Fast determination of biocatalyst process stability

Process Biochemistry 34 (1999) 535 – 547 www.elsevier.com/locate/procbio

Fast determination of biocatalyst process stability M. Boy *, A. Dominik, H. Voss SFB Biocatalysis, Institute of Biotechnology, Graz Uni6ersity of Technology, Petersgasse 12, A-8010 Graz, Austria Received 23 March 1998; received in revised form 17 September 1998; accepted 7 October 1998

Abstract A major bottleneck in developing industrial enzymes is the lack of a method for determining catalyst process stability quickly and efficiently. In order to solve this problem, a new method for the fast in-situ characterisation of activity and long-term stability has been developed. The necessary theory of modelling enzyme activation and deactivation is presented. As a model reaction we have chosen the carboxy-esterhydrolase-catalyzed hydrolysis of triglycerides. These reactions were performed in a fed-batch and continuous flow reactor. To accelerate the process of ageing, the temperature was continuously increased during the experiments. The procedure of parameter determination on the basis of experimental results is described for first-order, series and parallel deactivation mechanisms. Additionally, several criteria for choosing the applicable mechanism are presented. As an application of the new method, the influence of immobilisation on activity and stability of the immobilised enzymes was investigated. The temperature dependency of characteristics such as initial activity, half-life time and turn-over-number were determined. © 1998 Elsevier Science Ltd. All rights reserved. Keywords: Enzyme deactivation; Deactivation mechanism; Carboxy-esterhydrolase; Initial activity; Half-life time; In-situ characterisation

1. Introduction Immobilising enzymes on solid support materials is a very effective way to stabilise them. Immobilisation leads to heterogeneous systems which enable separation from the reaction media and continuous processing. Additionally, a significant change in the characteristic properties of the biocatalysts is observed. Hence, new additional possibilities for using enzymes in the pharmaceutical, chemical and food industry as well as for analytical purposes result. Most of the known immobilisation techniques were developed for laboratory use, however, and not for industrial applications. One major reason for this is the difficult determination of the long-time behaviour of the biocatalyst under process conditions. Different ways of changing activity, selectivity and stability of enzymes are known [1]. Important  The authors would like to dedicate this publication to the memory of Professor Harald Voss who passed away October 6, 1998. Professor Voss will always be remembered by his students and Colleagues for his enthusiasm and support. He will be greatly missed. * Corresponding author. Tel.: +43-316-8738415; fax: + 43-3168738434. E-mail address: [email protected] (M. Boy)

factors are temperature, inhibitors, ionic strength, pH, flow environment and reaction solvent. In general, however, much experimental effort is required to determine these phenomena [2]. In the development of carrier-bound biocatalysts highly active, selective and stable biocatalysts should be achieved [3,4]. In particular, the determination of these properties is difficult, often inaccurate and expensive [5]. Therefore, recent research interest has been focused on finding new, more rapid and accurate methods [6]. To solve this problem, a new method for fast in-situ characterisation of activity and long-term stability of enzyme carrier catalysts regarding the temperature is presented in this paper. Common methods are working at a constant temperature which lead to a (quasi-) stationary operating point in a long-term experiment (Fig. 1). Using this approach the information is restricted to one half-life time at the experimental temperature. Characterising stable enzymes for industrial purposes at a low and medium temperature range will take months up to years and so only a few spot-checks are taken. A rational design of enzymes and enzymecarrier-combinations is not possible. To circumvent this limitations a method for the complete characterisation

0032-9592/99/$ - see front matter © 1998 Elsevier Science Ltd. All rights reserved. PII: S 0 0 3 2 - 9 5 9 2 ( 9 8 ) 0 0 1 2 4 - 1

536

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

Fig. 1. Comparison of dynamic shift-techniques with common methods.

of a biocatalyst in a wide temperature range within a short time was developed to accelerate the process of ageing the temperature was increased continuously during the experiment. The experimental result of this approach is an instationary system response. The evaluation process consists of different steps. Based on the experimental results, a deactivation mechanism is assumed and the corresponding mathematical model formulated. For determination of the model parameters based on the experimental results each section of the system response has to be evaluated with different algorithms. Finally, it is possible to calculate the biocatalysts characteristics. Working under industrial process conditions allows one the determination of the relevant information necessary to characterise the carrier-bound biocatalyst. This knowledge allows the design and optimisation of biocatalytic industrial processes within a short period of time [7]. The structure in this paper is oriented to the evaluation procedure of the dynamic shift-techniques in Fig. 1. First-order, series and parallel deactivation mecha-

nism and the corresponding mathematical models are presented. After description of materials and methods the parameter estimation procedures for each deactivation mechanism is described. Finally some results regarding the influence of immobilisation are presented as possible applications using this fast method for the Accelerated Measurement of Activity and Stability of Enzymes (AMASE).

2. Modeling enzyme activation and deactivation Enzyme deactivation can be described by the following general deactivation scheme [1]: k1

k2

k3

E1 c k

E1 kc

E1 kc

¡kd1 E D1

¡kd2 E D2

¡kd3 E D3

−1

−2

−3

···

km

c Em

k−m

¡kdm E Dm

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

537

2.1. First-order deacti6ation The simplest mechanism is a single step enzyme deactivation. Reversible deactivation of the native and active enzyme EN is assumed. The equilibrium constant K gives the ratio of reversible deactivated enzyme ED* and EN. The sum of EN and ED* deactivates irreversibly to ED with the deactivation rate coefficient kd.

ÆE N Ç k d à 6 K à “ ED ÈE*D É

Fig. 2. Scheme of the experimental plant.

EN is the single and native form and Ei (i =l…m) is some intermediate form which is stable and active. EDi represents a final, completely deactivated form. All forms are connected by the forward and reverse deactivation rate constants ki, k − i, and the final deactivation rate constant kdi, respectively. All of the presented deactivation mechanisms can be derived on the basis of this general scheme. The object of this paper is to demonstrate a common method which is applicable for different mechanisms. To prove the general validity, three different mechanisms were selected. Theoretical basics for first-order, two step series and parallel deactivation mechanisms are presented. The parameter estimation procedure is demonstrated for each case.

In mathematical terms the mechanism can be described by a mass balance and a differential equation: [E] =[E*D ]+ [EN]

(1)

d[E] = −kd · [E] dt

(2)

At the beginning of the process the whole enzyme is in the native form: [E]0 = [EN]0

(3)

The deactivation rate coefficient kd and the equilibrium constant K are temperature dependent according to the Arrhenius law: kd = kd, · e

E − d,irr R·T

Fig. 3. Cleavage of tributyrin by Novozyme 388 immobilised on organopolysiloxane.

(4)

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

538

Fig. 4. Cleavage of olive oil by Lipozyme IM.

[E*D ] =K [EN]

(5)

K = K · e

−

r= f(T, Ci, Cenzyme)= f1(T) · f2(Ci ) · f3(Cenzyme)

(7)

A frequently used expression for the kinetics of enzymic reactions is the Michaelis-Menten-equation. r = rmax ·

[ci ] Km + [ci ]

(8)

It is possible to define the maximum reaction rate as a product of rate coefficient for the enzyme-catalysed reaction kr and the native enzyme concentration [EN]: rmax =kr · [EN] Separable enzyme kinetics can be expressed as:

(11)

f3(cenzyme) [EN]

(12)

(6)

In addition to reversible and irreversible enzyme deactivation, the biochemical reaction is also a function of temperature. In general, the biochemical reaction rate can be expressed in separable terms of temperature T, substrate concentrations ci and enzyme concentration cenzyme (Eq. (7)). Other factors influencing the biochemical reaction rate are inhibitor concentration, pH-value, etc., but for the development of the method to characterise the temperature effects we concentrated on temperature, substrate and enzyme concentration.

(10)

[ci ] KM + [ci ]

f2(ci )

Ed,rev R·T

f1(T) kr

In the case of substrate saturation Eq. (8) simplifies to Eq. (13). In general, the substrate and product concentrations may effect the inactivation rates [8], but in the case of the chosen model enzyme only minor effects were found. To fulfil the assumption of substrate saturation adequate substrate concentrations and flow rates were chosen during the experiments. r=rmax = kr · [EN]

(13)

The definition of the specific enzymic activity a (mol g − 1 per s) a=

rmax [E]0

(14)

and Eq. (13) together with Eq. (15) for the temperature dependence of the rate coefficient kr. kr = A · e

−

Ea R·T

=A

(15)

finally leads to:

(9) a= A ·

E [EN] [E ] − a = A · e R·T · N [E]0 [E]0

(16)

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

539

Fig. 5. Arrhenius-plot of the specific activity during the period of increasing activity.

The set of equations Eqs. (1) and (6) and Eq. (16) allows the calculation of the time course of the specific enzymatic activity dependent on temperature.

2.3. Parallel deacti6ation

2.2. Series deacti6ation The next mechanism presented is series deactivation. The native enzyme EN decays to the active intermediate E1 of a different activity before it deactivates to the inactive form ED. Each step of the series deactivation is assumed to be first-order. kd,1

kd,2

EN “ E1 “ ED The following set of differential equations can be derived: d[EN] = − kd,1 · [EN] dt

(17)

d[E1] =kd,1 · [EN]−kd,2 · [E1] dt

(18)

At the beginning of the process, the whole enzyme is in the native form. The temperature dependency of the deactivation rate coefficients for each fraction follows the Arrhenius law corresponding to equation (4). The specific activity thus has to be defined as the weighted specific activity of both enzyme fractions. a=xN · AN(T)+x1 · A1(T) =xN · AN, · e xN =

[EN] ; [E]0

E − a,N R·T

x1 =

[E1] [E]0

+x1 · A1, · e

activity for a series deactivation mechanism can be determined.

E − a,1 R·T

(19) (20)

Using the equations presented together with mass balances for the enzyme forms, the time course of enzymic

For industrial purposes the use of raw enzyme preparations is quite common. It is possible that such preparations contain related enzymes with the same catalytic function, but different properties regarding activity and stability. Parallel deactivation of two enzyme fractions is the third relevant mechanism considered in order to demonstrate the validity of the method presented. Both enzyme fractions deactivate according to a first-order mechanism to a final, inactive form ED,i.

Á E N1  k d à 6 K à “1 ED1 ÄE D*1 Å kd

EN2 “2 ED2 Enzyme fraction E1 exhibits an additional reversible deactivation step as already described (Eq. (1)–(6)). For the second enzyme a simple first-order deactivation mechanism is assumed. The following equations can thus be conceived: [E1]= ÈED*,1É +ÈEN,1É

(21)

d[E1] = − kd,1 · [E1] dt

(22)

dÈEN,2É = −kd,2 · [EN,2] (23) dt Assuming the activation coefficients of the enzymic reaction are equal (AN,1 = AN,2 = A), the specific activity can be calculated as:

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

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Fig. 6. Cleavage of tributyrine by esterase EP10.

a=

A · (ÈEN,1É+ ÈEN,2É) [E]0

(24)

This assumption is a simplification of the general case which is necessary to evaluate the parameter of experimental data resulting from a ‘standard experiment’ (see Sections 3 and 4). To estimate different activation coefficients of parallel deactivating enzymes a change in the experimental temperature course is necessary to generate this information. The temperature dependency of the activation coefficient A and deactivation rate coefficients kd,i follows Arrhenius law corresponding to Eqs. (15) and (4), respectively.

3. Material and methods

3.1. Enzymes and chemicals The goal of the present study was to demonstrate the application of the newly developed method for investigating the kinetics of different deactivation mechanisms. Different carboxy-esterhydrolases which exhibit first-order, series and parallel mechanisms were investigated. A lipase of Mucor mihei was examined both as a free enzyme and immobilised on different carriers. Novozyme 388 (Novo Nordisk) was used as a free enzyme. Additionally, a carrier bound enzyme of this source is commercially available (Lipozyme Novo Nordisk). The support material is a highly porous anion exchanger resin of the phenolic type (particle size 0.2 – 0.6 mm). To compare different support materials,

Novozyme 388 was immobilised on a hydrophobic organopolysiloxane-carrier (DELOXAN®, propylsiloxane modified ethylenediaminopolysiloxane, particle size 0.2–0.4 mm, Degussa AG). The carrier was saturated 1 with 170 mgprotein g − dry carrier with a yield of 80%. A highly −1 active carrier-bound enzyme with 30 000 IU gdry carrier according to the tributyrine standard assay [9] was achieved. To investigate a parallel deactivation mechanism, an esterase EP10 [10] was examined as a free enzyme. The fermentation broth containing a genetically modified E. coli was disrupted by ultrasonic treatment, the cellular debris was separated by centrifugation and the supernatant used as a raw enzyme preparation. A specific activity of 60 IU ml − 1 was achieved using the tributyrine standard assay [9]. As a model reaction, the hydrolysis of triglycerides was chosen. Tributyrine (Fluka) was emulsified in water. Olive oil (Fluka) was emulsified in water. Preparation of the aqueous media was performed according to the literature [9].

3.2. Experimental conditions Experiments with free enzymes were carried out in jacket-cooled, flat-flange standard glass reaction vessels of 2000 ml total volume (Schott). A fed-batch process was used. The initial reaction volume was 200 ml. The feed rate depends on the enzymic activity. Substrate saturation should be achieved during the whole experiment. The feed rates to fulfil this assumption, the used enzyme amounts and the applied temperature programs are presented in Table 1. The feed rates were attained

Enzyme preparation

Enzyme source

Carrier material

Reactor type

Medium

Feed rate (ml h−1)

Enzyme amount

Temperature programme

Free enzyme Free enzyme Immobilized enzyme Immobilized enzyme Immobilized enzyme

Novozyme 388 Esterase EP 10 Novozyme 388

– – Organopolysiloxane Anion exchanger resin Anion exchanger resin

Fed-batch Fed-batch Continuous stirred tank reactor Continuous stirred tank reactor Continuous stirred tank reactor

Tributyrine Tributyrine Tributyrine

200 140 528

14 ml 1 ml 0.015 gdry

10–70°C in 7 h Const. 8°C for 2 h, 8–58°C in 7 h Const. 6.4°C for 2 h, 6.4–66.4°C in 7 h

Tributyrine

214

Lipozyme IM Lipozyme IM

carrier

0.499 gdry

10–70°C in 7 h

carrier

Olive oil in buffer

110

2.5 gdry

carrier

10–85°C in 8 h

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

Table 1 Experimental conditions

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M. Boy et al. / Process Biochemistry 34 (1999) 535–547

542

Table 2 Activation and deactivation coefficients of free and carrier-bound Mucor mihei lipase Activation coefficients

Novozyme 388 Novezyme 388/organopolysiloxane Lipozyme IM

Deactivation coefficients

A (mol g−1·per s)

Ea (kJ mol−1)

K [–]

Ed,rev (kJ mol−1)

kd, (1 s−1)

Ed,irr (kJ mol−1)

175.5 13.45

32.53 26.74

3.656×1019 7.567×1021

120.52 134.44

5.231×1033 6.733×1038

231.79 262.66

16.5×104

60.19

1.363×1019

114.50

1.617×1049

328.10

by a gear pump (MC-Z, Ismatec). The substrate solution was stored under stirring on a magnetic stirrer in a ice bath. The speed of the 3-blade-impeller stirrer with 70 mm diameter was 300 rpm. Temperature control was reached by a computer controlled external heating bath. pH was maintained at 8 using an autotitrator (Schott Titroline). 0.1 mol l − 1 potassium hydroxide solution was used as titrant. For use of immobilised enzymes in a continuous processes, a jacket-cooled, flat-flange standard glass reaction vessel with 500 ml total volume (Schott) and 250 ml working volume was used. 300 rpm stirrer speed with the 3-blade-impeller stirrer with 70 mm diameter was found to be enough to overcome external mass transfer resistance. The flow rate depends both on enzymic activity and the amount of enzyme used. Flow rates, enzyme amount and temperature programs are presented in Table 1. The feed was attained by a gear pump (MC-Z, Ismatec). The working volume was held constant by pumping out the excess solution with a vacuum filtration aspirator pump through a glass frit. Due to higher activity, 1 mol l − 1 potassium hydroxide solution was used as titrant to hold the pH-value constant at 8. The experimental arrangement is shown in Fig. 2. The time course of titrant necessary to neutralise the fatty acids produced is automatically recorded, corrected and converted into activity.

4. Parameter estimation

4.1. First-order deacti6ation Fig. 3 shows the measured and simulated specific activity, the temperature profile and the computed concentration of native enzyme of the lipase Novozyme 388 immobilised on organopolysiloxane. In order to determine the temperature dependent coefficients of Eqs. (4), (6) and (16), the measured specific activity is evaluated in sections. In the first time-interval (2 –4.5 h) it is possible to neglect reversible and irreversible deactivation of the enzyme because of the low temperature (6 – 26°C) and short operation time. This assumption leads to

[EN]/[E]0 = 1.

(25)

Eq. (16) finally simplifies to: Ea

/

a= A · eR·T

(26)

By printing the specific activity during this time interval in an Arrhenius plot, the activation coefficients A and Ea could be determined. With increasing temperature the fraction of reversibly deactivated enzyme increases. Irreversible deactivation plays a minor role because of moderate temperature and operation time. A mass balance of the enzyme leads to: [E]0 = [EN]+ [ED* ]

(27)

Combining Eqs. (5) and (27) with Eq. (16) results in Eq. (28) to determine the equilibrium constant K: A · e K=

a

−

Ea R·T

−1

(28)

During the time interval between 5 and 6.2 h the equilibrium constant K could be calculated from the measured specific activity a and the previously determined activation coefficients A and Ea. An Arrhenius plot of K leads to the reversible deactivation coefficients K and Ed,rev. At the end of the temperature programme, the fraction of irreversibly denaturated enzyme increases. When combining equations Eqs. (1), (2), (5) and (16), one finally obtains a formula allowing an evaluation of the coefficients of irreversible deactivation.





1 d T 1 da K Ed,rev Ea kd = · − · − · 1+ K R R dt a dt

(29)

The equilibrium constant K is temperature dependent according to Eq. (6). During the time interval between 7 and 8 h, kd could be calculated from the measured specific activity a and the previously determined activation and reversible deactivation coefficients. The graphical presentation of kd in an Arrhenius plot leads to the determination of the irreversible deactivation coefficients kd, and Ed,irr.

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

543

Fig. 7. Relative initial activity of free and carrier-bound Mucor mihei lipase.

4.2. Series deacti6ation In Fig. 4 the measured and simulated specific activity, the temperature profile and the calculated concentrations of enzyme fractions EN and E1 of Lipozyme IM cleaving olive oil in an aqueous medium are presented. A characteristic for a series deactivation is the distinct activation before the maximum activity is reached. Enzyme fraction E1 is assumed to be stable compared to fraction EN. Both fractions are activated by different functions AN and A1. Assuming the initial fraction of enzyme E1 is zero (x1 =0 in Eq. (19)) and neglecting the irreversible deactivation of EN at the beginning of the process because of short time and low temperature, the overall specific activity during the first (0 – 2.5 h) period is related to the enzyme fraction EN. a = AN(T)=AN, · e

E − a,N R·T

(30)

Neglecting irreversible deactivation of E1 because of moderate temperature and operation time and assuming a total conversion of EN to E1, the second period (4.5 –6 h) is dominated by the activation of E1. a= A1(T)= A1, · e

E − a,1 R·T

(31)

The different time periods could easily be detected by plotting the specific activity during the period of increasing activity in a Arrhenius diagram. Each period has a different rate as shown in Fig. 5. From the

Arrhenius diagram the activation coefficients Ai, and Ea,i can be determined. The deactivation coefficients of enzyme fraction EN are calculated for the period of coexisting enzyme fractions EN and E1. By neglecting the irreversible deactivation of E1, a constant overall enzyme concentration can be assumed. [E]0 = [EN]+ [E1]= const.

(32)

This period could be detected in the previous Arrhenius diagram as the time interval at the point of intersection of both rates (2.7–3.7 h). The fraction of the native enzyme xN could be calculated by introducing Eqs. (19) and (20) in mass balance Eq. (32). If xN is known, the deactivation rate coefficient kd,1 can be determined according to the definition of irreversible first-order deactivation. kd,1 = −

1 dxN · xN dt

(33)

By plotting kd,1 in a Arrhenius diagram it is finally possible to determine kd,l and Ed,irr,1. Under the assumption that EN is completely transferred in E1, Eq. (34) can be used to calculate kd,2. This assumption is valid at the end of the process (6.5–8 h). The determination of kd, ,2 and Ed,irr,2 can be carried out in the same way as described for kd, ,1 and Ed,irr,1 using an Arrhenius diagram. 1 d 1 da E T kd,1 = · + a,1 · (34) a dt R dt

:

;

544

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

Fig. 8. Half-life time of free and carrier-bound Mucor mihei lipase.

4.3. Parallel deacti6ation Fig. 6 shows the measured and simulated specific activity, the temperature profile and the calculated concentrations of enzyme forms E1 and EN2 of esterase EP10. This enzyme preparation was used as raw enzyme, so a parallel deactivation mechanism of two sub-types of esterases seemed to be possible. Such a parallel deactivation of two different individual enzyme fractions is indicated by two distinct rates of decreasing activity at the end of the experiment. As has been shown for the first-order deactivation mechanism, it is possible to neglect reversible and irreversible deactivation of the enzymes fractions during the first time interval (2–2.5 h) because of the low temperature (8– 12°C) and short period of time. Determination of the activation coefficients A and Ea can be carried out in the same manner as was demonstrated for first order deactivation. For all further steps, EN,2 is defined as the stable enzyme fraction. At moderate temperatures (12 –18°C) and for relatively short periods of time (2.5 – 3.5°h), deactivation of EN,2 could be neglected. ÈEN,2É =ÈEN,2É0 =const.

(35)

The first derivative of Eq. (24) can thus be simplified: dA dÈEN,1É · ([EN,1]+[EN,2]) +A · da dt dt = dt [E]0

(36)

By introducing the first derivative of time of A (Eq. (15)) and employing the first-order deactivation kinetics of the less stable enzyme fraction E1 one now obtains: da E d1/T · a− kd,1 · a1 =− a R dt dt

(37)

When considering Eq. (35), the specific activity can be conceived as being a = a1 + a2,0 = a1 + A

[EN,2]0 = a1 + A · x2,0. [E0]

(38)

Eqs. (37) and (38) can now be combined to derive Eq. (39) in order to determine the deactivation rate of enzyme E1: 1 d da Ea T − − · ·a dt R dt kd,1 = a− A · x2,0

(39)

To be able to calculate kd,1, x2,0 must be known or estimated at the beginning of the process. If x2,0 is estimated, an additional optimisation step after the parameter estimation procedure is necessary to verify the determined parameters of the parallel deactivation model. At the end of the experiment (7–9 h), the unstable enzyme fraction E1 is totally denaturated ([E1]=0), resulting in Eq. (40) thus permitting one to calculate the deactivation coefficients kd,2, and Ed.2 from a Arrhenius diagram of kd,2.

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

:

1 1 da Ea T kd,2 = − + a dt R dt d

;

545

Fig. 9. Turn-over-Number (TON) of free and carrier-bound Mucor mihei lipase.

5. Results and discussion (40)

As demonstrated, the coefficient estimation procedure is mathematically and numerically intensive. In order to carry out this work, a software program was developed. This program enables the evaluation of more complex models such as the parallel deactivation of two enzyme populations with and without reversible fractions and series deactivation with and without reversible fractions quite easily. In an interactive procedure, the user manually chooses a period of time to calculate a certain parameter. The program then calculates the Arrhenius diagrams and all other pertinent parameters. Visual control of the plots allows one to decide whether or not a suitable period was used. The Arrhenius diagram clearly indicates if the underlying assumptions were correct. In this case it is possible to interpolate the measured values using a straight line. If not, the last step can be repeated, otherwise the procedure can be continued. At the end of the parameter estimation process, the determined kinetic and thermodynamic parameters are further improved by fitting the simulated activity to measured values. This optimisation step demonstrates the quality of the procedure developed for parameter estimation. In the case of the presented experiments, the average variation of the coefficients was about 5%. The maximum variation was 19%. The reproducibility and the precision of the whole method from the experiment up to the set of parameters was checked as well. In general, the experiments were performed three times which finally lead to a maximum overall difference of 9%.

5.1. Choosing a deacti6ation mechanism As has been demonstrated, parameter estimation is an intensive interactive procedure. In spite of the software developed it is still time consuming. To avoid having to check all deactivation mechanisms in this manner, some characteristics of the experimental results (specific activity versus time plot) allows discrimination between the mechanisms. The chosen temperature programme influences the time course of the specific activity, but neither the mechanism nor the parameters. A medium rate has to be found because a high rate leads to a steep increase of activity during activation and a steep decrease of activity during irreversible deactivation which makes parameter estimation difficult. On the other side, undesirable long experiments are the result of slow rates. First-order deactivation characteristically exhibit an regular increase of activity (2–4.5 h) and a steep decrease of activity after the maximum (6.5–8 h), as shown in Fig. 3. Typical for parallel deactivation mechanism is the presence of two distinct rates of decreasing activity after maximum activity. For example, such behaviour can be recognised as being present between 4–6.5 h and 6.5–9 h in Fig. 6. Fig. 4 shows a typical series deactivation mechanism which could be detected by an extended increase of activity with two distinctive rates (0–3.5 h and 3.5–6 h) and a steep decrease after the maximum (7–8 h). An additional indication is the fact that two different rates of the specific activity are to be found from an Arrhenius diagram, as shown in Fig. 5.

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

546

If no distinct characteristics could be detected, the possible mechanism which is actually present has to be estimated. In this case, calculating the standard deviation after parameter estimation as described before is a possibility to choose. Using non-linear regression procedures without estimating good initial parameters is not possible, because the parameters are of different orders of magnitude (see Table 1). It has to be stressed in general, that although the experimental results fit well, it is still no absolute proof for the proposed mechanism. It is not the claim of the presented method to prove mechanism, but to find a model with a set of parameters which fits the experimental data and can be used to calculate enzyme characteristics and process strategies.

5.2. Process de6elopment using the new method To demonstrate the applicability of the new method, some important questions in developing industrial biocatalytic processes were examined. One particular decision is whether to use free or immobilised enzymes and the choice of the carrier material in the case of immobilisation. The design of the reaction media plays a major role in the biocatalytic process itself as well as for enzymic activity and stability. With common methods it is impossible to quantify the costs of the biocatalyst as a function of temperature, pH-value, solvent, etc. quickly and efficiently.

5.3. Influence of immobilisation The presented method was used to determine the influence of immobilisation on the lipase. For all experiments carried out to determine the influence of immobilisation, a first-order deactivation mechanism with a reversible deactivation was found to be the best fitting one. The coefficients of the different immobilised and free enzymes are presented in Table 2. Depending on the method of immobilisation, different coefficients, of activation and deactivation were found. These coefficients were used to calculate characteristic values such as initial activity (Fig. 7), half-life time (Fig. 8) and the utilisation of the biocatalyst depending on the temperature. To quantify the utilisation of the biocatalyst a Turn-over-Number (TON) was defined. TON expresses how much substrate can be converted until a defined residual activity is reached. TON=

&

t(a = amin)

a(t) dt

(41)

0

For example, the residual activity can be given by a minimum conversion with a fixed amount of enzyme used in a reactor. Fig. 9 shows the TON dependence on temperature.

When examining the initial specific activity, one has to keep in mind that for reasons of clarity the initial specific activity of Lipozyme IM was plotted on a separate axis. Maximum initial activity for the free lipase (Novozyme 388) and organopolysiloxane-bound lipase is 50 times higher than for Lipozyme IM. Optimum temperature (41°C) is independent of immobilisation. The lipase seemed to be best bonded on the carrier in the Lipozyme IM preparation since the absolute change in initial specific activity is much lower in comparison to the free and organopolysiloxane-bound enzyme. However this strong bonding leads to low activity. The highest half-life time at low temperatures has also been found for Lipozyme IM (Fig. 8). The comparable course of half-life time for the free enzyme and organopolysiloxane-bound enzyme indicate a weak bonding of the enzyme on the carrier. Again, the higher activity compared to Lipozyme IM has to be taken into account. Fig. 8 clearly shows the big advantage of the presented method for fast in-situ characterisation of activity and long-term stability. The half-life of Lipozyme IM at 30°C is about 140 days. This period is necessary to measure the half-life time in an isothermal experiment. To determine the half-life times of Lipozyme IM in the whole temperature range from 10 to 70°C in 10°C intervals using the common isothermal techniques would take about 3700 years (of course, even during 140 days other phenomena beside thermal deactivation (e.g. microbial growth) may be responsible for shorter half-life times). To get the same information using the new method one 12 h-experiment is sufficient. Fig. 9 shows the TON of free and immobilised Mucor mihei lipase. 300 U g − 1 was defined as minimum specific activity. In contrast to free and immobilised Novozyme 388, the initial specific activity of Lipozyme IM reaches this lower level only in the temperature range between 28 and 54°C (Fig. 7). Therefore, calculation of TON is restricted to this range. Lipozyme IM reaches a maximum in the temperature course of the TON. This temperature is an optimum operation point if the costs of the enzyme plays an important role in the overall process. Below the optimum, the same TON can be reached at two temperatures, e.g. 5× 108 mmol g − 1 at 29 and 35°C. At 29°C −1 the initial specific activity is 315 U gdry carrier (Fig. 7). In contrast, at 35°C the initial specific activity is about 410 U g − 1, but because of the higher temperature, the enzyme deactivates much faster. By maintaining the effectivity of the enzyme constant, it is possible to take other factors such as side reactions or initial reaction rate into account. The free and immobilised Novozyme 388 shows a regular decay of the TON over the whole temperature range. With rising temperature, the deactivation increases and the TON decreases. There is no observable optimum since the initial specific activity

M. Boy et al. / Process Biochemistry 34 (1999) 535–547

over the whole temperature range is much higher than the defined minimum specific activity of 300 U g − 1. As shown in Fig. 7 – (9) when using the new developed method it is an easy way to check different ways of immobilisation quickly and efficiently regarding activity and process stability. Considering the costs of immobilisation, it is possible to optimise the costs of the catalyst. The procedure for developing carrierbound biocatalysts for industrial purposes can thus be dramatically accelerated.

6. Conclusions The newly developed method for fast in situ characterisation of activity and long-term stability of enzyme carrier catalysts enables producers and users of enzymes and carrier-bound enzymes to characterise biocatalysts quickly and, therefore, accelerates the process of choosing and developing carriers. Commercially available biocatalysts could be very easy characterised for a special problem. A quick process optimisation regarding process conditions, reaction media and finally the costs of the catalyst thus becomes possible. Symbol A a amin cenzyme ci E1…En Ea Ed,irr Ed,rev K Km kd kr

activation coefficient [mol g−1 per s] specific enzymatic activity [mol g−1 per s] residual specific enzymatic activity [mol g−1 per s] enzyme concentration [g l−1] concentration of substrate i [g l−1] enzyme fractions l…n activation enthalpy [kJ mol−1] activation enthalpy of irreversible deactivation [kJ mol−1] activation enthalpy of reversible deactivation [kJ mol−1] equilibrium constant [–] Michaelis-Menten-constant [g l−1] deactivation rate [l s−1] rate of reaction [l s−1]

R r rmax S T t xi Subscribes oo 0 1…m D D* N []

547

gas constant [kJ mol−1 per K] reaction rate [mol l−1 per s] maximum reaction rate [mol l−1 per s]. substrate concentration [mol l−1] temperature [K] time [s] part of enzyme fraction in on the whole enzyme population [–] reference conditions refers to t=0 refers to enzyme fraction 1…m irreversibly deactivated reversibly deactivated native refers to enzyme concentration [g l−1]

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