Engineering and Manufacturing for Biotechnology - Marcel Hofman & Philippe Thonart

Metabolic investigation of an anaerobic cellulolytic bacterium

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Creuly C. Pons A. and J.M., Dussap

3.2. FLUX CALCULATION

The biochemical composition and the macrocomponents biochemical composition of

Fibrobacter succinogenes are unknown. The data representing an average composition of the bacteria Escherichia coli established by Neidhardt (1987) have been used:

The matrix built with the above metabolic network is a matrix, with 108 compounds, 96 reactions, 13 exchangeable and 95 non-exchangeable compounds. After all steps of computing analysis, the rank of the square matrix is 96. We have considered eight exchangeable compounds to make data reconciliation: glucose, acetate, succinate, formate, cellobiose, cellotriose, and biomass.

Yield products are calculated and used as experimental data in the program of metabolic flux calculation associated with the data reconciliation method. In Table 2, the key fluxes of central metabolism are reported. The fluxes are thermodynamically consistent, i .e. no negative flows in irreversible reactions.

3.3. VALIDATION

Validation of this model is obtained by comparison between the theoretical yields of carbon elements calculated by computed flux program and the experimental yields measured during anaerobic culture of Fibrobacter succinogenes (Table 3). This table shows a good correlation between yields values of the main products of metabolism (succinate, acetate and formate). These results validate the metabolic network proposed in Figure 1. An other interesting information given by the flux data is that carbon dioxide is consumed and not produced by this bacteria with a consumption ratio of

glucose.

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Metabolic investigation of an anaerobic cellulolytic bacterium

The major difference is observed on the estimation of biomass between the experimental and computed yields. The best value may be the calculated value because it is correlated to the actual consumption of that validates the previous biomass elemental composition. The mass balance calculation imposes directly a calculated yield of 5.58 g biomass / g The deviation with biomass measurement could be assigned to the experimental indetermination of glycogen and cellodextrins. In fact, when extracellular sugar concentration is high, part of the sugar is stored as glycogen (Gaudet et al, 1992). This glycogen storage can represent as much as 70% of the total dry mass of the bacteria and it seems to be included in our experimental value of biomass determined by dry matter.

Glucose is also released as cellodextrins via cellobiose into the external medium (Wells et al, 1995). These authors evidenced cellodextrin synthesis from cellobiose as substrate but cellodextrins were also synthesised when glucose was the sole carbon source (Matheron et al, 1996). This entails that the first step of cellodextrins synthesis is catalysed by the cellobiose phosphorylase that is able to condense one glucose and one glucose 1-phosphate into cellobiose. Larger cellodextrins may then be synthesised by cellobiase activity. This polysaccharide would be precipitated with cell mass during the step of centrifugation and subsequently majored experimental value of biomass.

4. Conclusions and perspectives

This fed-batch process enables to produce more than 0.15 g biomass per g glucose. This value would be improved by a more complete understanding of Fibrobacter succinogenes metabolism. The first step was the development of the metabolic network.

There is a satisfactory agreement between theoretical and experimental mass balance data. Though the oxidative part of pentose pathway has not been included in the network, the calculated distribution of metabolic flux satisfies thermodynamic consistency for all reactions. The pentose requirements of metabolism are supplied through glyceraldehyde 3-P and acetyl 1-P as metabolic intermediates (Table 1 - J76) which is a specific reaction of these bacteria.

This utilisation of a metabolism model to simulate the growth of this microorganism presents a new approach for strict anaerobic bacteria and allows to predict some data

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Creuly C. Pons A. and J.M., Dussap

that are difficult to measure in anaerobic conditions, such as the carbon dioxide uptake yield. In the same way, we show the difficulty to obtain an experimental value of the biomass concentration; the model calculates this value.

The metabolic model should be a useful tool to provide information about how the overall flux distribution will be affected by various growth conditions and specially with various substrates. Glucose and cellobiose, final products of cellulose degradation, are taken up and metabolised by the cells into succinate, acetate and formate (Gaudet et al., 1992). In vivo -NMR spectroscopy has been used successfully to investigate metabolism of various microorganisms (Matheron et al., 1996). This technique allows identification of enriched molecules and, more precisely, localisation of the labelling in the molecule. Thus, the use of a specifically labelled substrate allows a detailed description of the metabolic pathway that it enters. The quantitative determination of metabolic fluxes by NMR experiments has shown the reversibility of different metabolic pathways: reversibility of glycolysis, reversibility of the succinate synthesis pathway and futile cycle of glycogen (Matheron et al., 1999). But all these measurements have been carried out with resting cells in order to maintain suitable in vivo NMR conditions. This study, performed from an overall determination of yields and a biochemically structured model, enables to extend the previous results for resting cells to a growth situation obtained in controlled bioreactor.

In a near future, this approach could be improved by focusing attention and developing theoretical tools in parallel with experimental bioreactor in two directions:

•further investigations about biochemically structured metabolism : and NMR experiments have to be carried out with the aim of collecting new information about the metabolism of the rumen cellulolytic bacterial strains, particularly the carbohydrate metabolism which seems to present interesting specificity ;

•development of quantitative aspects of polymerised and lignified substrates digestion, such as digestion of cellobiose, crystalline cellulose and straw feed.

For more complex substrates, we will have to include in the model the simultaneous but differential consumption of sugars. For example, the relative contribution of glucose and cellobiose to metabolite production, glycogen storage, and cellodextrins synthesis is not known but it would have to be predicted.

This will allow direct monitoring of the metabolism towards the production of biomass and esterases in conditions of bioreactors performances. The metabolic control aspects will certainly help for the development and control of a biotechnological process that is efficient in degrading lignocellulosic wastes.

Acknowledgement

The Centre National de la Recherche Scientifique, France, supported this work.

References

Bryant M.P. and Doetsch R.N. (1954) A study of actively cellulolytic rod-shaped bacteria of the bovine rumen, J.Dairy Sci., 37, 1176-1183.

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Chesson A. and Forsberg C.W. (1997) Polysaccharide degradation by the rumen microorganisms, Hobson, P.N., Stewart, C.S., the Rumen Microbial Ecosystem, 2nd ed. Blackie Academic. London, 329-381.

Dussap C.G., Pons A., Pequignot C. and Gros J.B. (1997) Application d’une méthode de réconciliation de données à des cultures menées en fermenteur discontinu, Récents Progrès en Genie des Procédés, 11, 7- 12.

Gaudet G., Forano E., Dauphin G. and Delort A.M. (1992) Futile cycle of glycogen in Fibrobacter succinogenes as shown by in situ NMR and NMR investigation, Eur.j.Biochem., 207, 155-162.

Glass T.L. and Sherwood J.S. (1994) Phosphorylation of glucose by a guanosine-5’-triphosphate (GTP)- dependent glucokinase in Fibrobacter succinogenes S85, Arch. Microbiol., 162, 180-186.

Gottschalk G. (1986) Bacterial metabolism. 2nd ed, Springer-Verlag, New-York.

Hungate R.E. (1950) The anaerobic mesophilic cellulolytic bacteria, Bacteriol.Rev., 14, 1-49.

Joyner Jr A.E. and Baldwin R.L. (1966) Enzymatic studies of pure cultures of rumen microorganisms,

Matte A., Forsberg C.W. and Verrinder A.M. (1992) Enzymes associated with metabolism of xylose and other pentoses by Prevotella (Bacteroides) ruminicola strains, Selenomenas ruminantium D and Fibrobacter succinogenes S85, Can.J.Microbiol., 38, 370-376.

Matheron C., Delort A.M., Gaudet G. and Forano E. (1996) Simultaneous but differential metabolism of glucose and cellobiose in Fibrobacter succinogenes cells, studied by in vivo 13C-NMR,

Can.J.Microbiol., 42, 1091-1099.

Matheron C., Delort A.M. and Forano E. (1999) Interactions between carbon and nitrogen metabolism in

Escherichia coli and Salmonella typhimurium, vol.1. American Society for Microbiology, Washington, DC.

Pons A., Dussap C.G., Pequignot C. and Gros J.B. (1996) Metabolic flux distribution in Corynebacterium melassecola ATCC 17965 for various carbon sources, Biotechnol.Bioeng.,51, 177-189.

Selinger L.B., Forsberg C.W., Cheng K.J. (1996) The rumen : a unique source of enzymes for enhancing livestock production, Anaerobe, 2, 263-284.

Stewart C.S. and Flint H.J. (1989) Bacteroides (Fibrobacter) succinogenes. A cellulolytic anaerobic bacterium from the gastrointestinal tract, Appl.Microbiol.Biotechnol., 30, 433-439.

Vallino J. J. and Stehanopoulos G. (1990) Flux distribution in cellular bioreaction networks : application to lysine fermentations. pp-205-219. In : S.K.Sikdar, M.Bier, and P.Todd.(eds.), Frontiers in bioprocessing.CRC Press, Boaca Raton, FL.

Wells J.E., Russel J.B., Shi Y. and Weimer P. J. (1995) Cellodextrin efflux by the cellulolytic ruminal bacterium Fibrobacter succinogenes and its potential role in the growth of non adherent bacteria,

Appl.Environ.Microbiol., 61, 1757-1762.

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Serpil Takaç, Sema Elmas, Tunçer H. Özdamar

enhanced. Process parameters such as protein concentration, transmembrane pressure (TMP), pH, ionic strength, temperature, shear rate, membrane material and structure have significant effects on ultrafiltration (Flaschel et al., 1983).

The literature covers information on the separation of different protein macromolecules that reports on the fouling mechanism (Pradanos et al., 1996; Boyd and Zydney 1998), adsorption mechanism (Gekas et al., 1993; Pradanos and Hernandez, 1996), transport phenomena (Henriksen and Hassager 1993; Saksena and Zydney 1997) and process parameters (Pradanos et al., 1992 and 1994; Pradanos and Hernandez 1995). Serine alkaline proteases (SAP; E.C.3.4.21.14) produced by the genus Bacillus are the most important group of industrial enzymes (Kalisz 1988) and the separation yield of extracellular SAP from biomass, other proteins, salts and impurities is important. Recovery of protease enzymes from fermentation medium usually includes stepwise procedure where ultrafiltration is an intermediate step. Gnosspelius (1978) reported 96% recovery of the protease enzyme from Myxococcus virences in the ultrafiltration step of the purification sequence. Manachini et al., (1988) investigated the separation of Bacillus termoruber alkaline protease from fermentation medium and reported 85% yield in the ultrafiltration step of the separation sequence. Sheehan et al., (1990) developed a two-stage pilot scale membrane filtration process to recover bacterial cells followed by ultrafiltration of an extracellular protease from fermentation broth and investigated the effect of transmembrane pressure and recirculation rate on the ultrafiltration performance. Bohdziewich (1994) studied the purification of Proteopol BP-S, a commercial preparation of proteolytic enzymes, with polyacrylonitrile membranes and reported the optimum values for TMP, flow velocity and temperature for the ultrafiltration. Although the information on the ultrafiltration of protease enzymes from fermentation medium is limited, a number of studies on the ultrafiltration conditions of several proteins provide important insights into how to select the optimal conditions for effective protein separation. Rodgers and Sparks (1991) investigated the effect of negative transmembrane pressure pulsing on solute rejection for an albumin and gamma-globulin mixture in ultrafiltration. Reis et al., (1997) studied various limitations of membrane systems for protein purification such as buffer composition, fluid dynamics; and reported on the optimisation of high performance tangential flow filtration of proteins. Burns and Zydney (1999) investigated the effect of solution pH on the transport of globular proteins with different surface-charge characteristics and molecular weight through ultrafiltration membranes.

In our previous study, we reported the separation from fermentation medium of extracellular SAP enzyme produced by Bacillus licheniformis using a crossflow ultrafiltration system. 30 000 and 10 000 Da MWCO polysulphone membranes were used to separate SAP from high molecular weight enzymes and low molecular weight organic acids and amino acids, respectively (Takaç et al., 2000). The effects of transmembrane pressure, recirculation velocity and enzyme concentration on the permeate flux, on the activities of enzymes, and on the recovery of SAP were investigated. In the present work, we performed further studies to develop the ultrafiltration process conditions to separate SAP from accompanying high molecular weight enzymes i.e., neutral protease and amylase enzymes in the B.licheniformis fermentation medium by using 30 000 Da MWCO polysulphone membrane. We

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Crossflow ultrafiltration of B. licheniformis medium to separate protease enzymes

investigated the effect of enzyme concentration and recirculation velocity on the permeate flux, on the total resistance, and on the recovery yield of SAP.

2. Materials and methods

2.1. EXPERIMENTAL RUNS

B. licheniformis (DSM 1969) cells were grown and inoculated as described elsewhere

(Çalik et al., 1998). The shake flask culture was transferred into the fermentation

and The initial pH of the medium was adjusted to 7.6 with 0.04 mol buffer. The laboratory-scale 3.5 batch bioreactors (Chemap CF 3000, Switzerland) were operated at 37°C temperature, 750 agitation rate and 1 vvm aeration rate conditions for 40 h in the cultivation for the production of protease

enzymes. After harvesting cells by centrifugation at 8000xg at (RC28S; Sorvall, Wilmington, DE), the fermentation medium was subjected to crossflow ultrafiltration in a flat modular configuration ultrafiltration device (Sartocon Mini SM 17521, Sartorius, Germany) by using 30 000 Da MWCO asymmetric polysulphone membrane. The experimental set-up is given elsewhere (Takaç et al., 2000). The solutions of different initial enzyme concentrations were tangentially driven over the membrane surface and recirculated with several rates. The permeate flux was collected in the permeate tank while the retentate was recycled back to the feed-retentate tank. The variation in the permeate flux with time was followed and the results were analysed with the cake resistance model. Ultrafiltration runs were terminated when a constant permeate flux was obtained. At the end of each experiment, the activity of SAP enzyme was measured off-line by taking samples from the permeate and feed-retentate tanks (Elmas 1997). Following each run, the membrane was rinsed with distilled water, with Sartocon Cleaning Agent 17639 (1.5%) and with formaldehyde solution (2-3%) in sequence.

Prior to ultrafiltration runs, the water flux was measured in order to calculate the hydraulic resistance for determining the cleaning efficiency.

2.2. ANALYSES

SAP activity was measured in borate buffer with casein (0.5%) at 37ºC. 2 cm3

solution for 20 min. Precipitated protein was removed by centrifugation for 15 min at

9000xg and then the absorbance of the supernatant was determined at (UV-

Shimadzu 160A, Tokyo, Japan). One unit of enzyme activity was defined as the activity that liberates 4 nmol tyrosine per min per . The protein content of the samples that was assumed to be equal to the total enzyme concentration was determined by the method of Lowry (Lowry et al., 1951) with BSA as the standard.

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Serpil Takaç, Sema Elmas, Tunçer H. Özdamar

2.3. CAKE RESISTANCE MODEL

Crossflow ultrafiltration is a pressure-driven process and gel polarisation, cake resistance, and osmotic pressure models characterise the process. According to the cake resistance model the solute rejected at the membrane surface results in the accumulation of molecules on the membrane, which leads to formation of a cake layer. The permeate flux (J) that is defined as the volumetric flow rate per unit area of the membrane may be expressed by Eq. (1):

where is total resistance, which is sum of the resistance of the membrane and the resistance due to cake layer; is the transmembrane pressure; and is the osmotic pressure difference. Since the osmotic pressure for macrosolutes are usually low, Eq.(l) is reduced to Eq.(2).

In these equations is defined as:

flux obtained after a period of ultrafiltration time in Eq.(2). Since the hydraulic resistance of the membrane was constant in all experiments as a result of effective

3.Results and Discussion

3.1.EFFECT OF INITIAL ENZYME CONCENTRATION

The effect of initial total enzyme concentration on the permeate flux was investigated for 0.153 and 0.166 values at kPa TMP and 0.5 recirculation velocity. Different gradual decreases in the fluxes were seen depending on

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