Fundamental of Immobilization Technology

It is well known that pure enzymes change their behavior, their stability, when they are immobilized. In the past two decades the immobilization of microorganisms, cells and parts of cells was gradually introduced into microbiology and biotechnology.

According to A.H. Scragg (1988) many of the cell immobilization techniques are modifications of the techniques developed for enzymes. However, the larger size of microbes has influenced the techniques. As for immobilized enzymes two broad types of methods have been used to immobilize microorganisms: attachment to a support and entrapment.

Table 1: Methods of Immobilization

Attachment

Without support Aggregation of floc for formation of cross-linking

With support Co-valent binding

Adsorption to ion-exchangers or inorganic

Biofilm formation

Entrapment Organic polymer

Inorganic polymer

Semi-permeable membrane

Immobilization of Microorganisms by Covalent Coupling

By these methods microorganisms are crossliked by chemical substances, e.g., by glutardialdehyde. The surfaces (especially the proteins) of microorganisms are liknked with the surfaces of other microorganisms by aldehyde groups of glutardialdehyde. Yeast cells, for instant, react with free ε-amino group or N-terminal amino groups to form imines. Another reaction mechanism was proposed concerning a conjugated addition of amino groups to double linkages of ε-,β-unsaturated oligomers, which are present in commercial aqueous solution of glutardialdehyde. This mechanism may explain the stability of the linkages. By this chemical linking, growth inhibition and toxic influences on the microorganisms are very intensive. These reactions are only partly understood and can lead to decay or death of the microorganisms.

Table 2: Microbial cells covalently linked to various supports

Species Support Product

Actobacter Metal hydroxides Acetic acid

Aspergillus niger Glycidyl methacrylate Gluconic acid

Micrococcus luteus CM-cellulose Urocanic acid

Saccharomyces cerevisiae Aminopropyl silica Ethanol

Saccharomyces cerevisiae Hydrocyalkyl methacrylate Killer toxin

Saccharomyces cerevisiae Cellulose Ethanol

Zygosaccharomyces lactis Hydroxyalkyl methacrylate β-galactosidase

Oxygen Transfer to Immobilized Microorganisms

Availability of oxygen is one of the most important parameters which are different for immobilized and free microorganisms. Free organisms can get oxygen directly from the surrounding air or, in most technical processes, from the liquid, especially water, which contains dissolved oxygen. The transfer dn/dt can be described by the following equation:

(1)

k_La is the volumetric oxygen mass transfer coefficient, dut to the oxygen transfer from the gas phase or air, c_g, the surface of the cells, c_x or to the transfer of oxygen dissolved in water to the surface of the cells.

In principle, the same formula can be applied to immobilized microoraganisms, but here the conditions are quite different. The adsorbed cells form microbial films or varying thickness during a short incubation time. Oxygen has to be transferred into these microfilms, and due to this, zones of different oxygen concentration in the films exist, in which the growth of the microorganisms varies in direct relation to the oxygen concentration.

As suggested by Mark R.Riley et.al., (1995), the diffusion and reaction processes taking place within immobilized cell systems can be analyzed by an effective equation of the form:

(2)

where C is the concentration of a metabolite (oxygen or glucose), D_eff is the effective diffusivity of the metabolite, and R(C) is the rate of metabolite consumption by the cells. By using this model, the maximum oxygen penetration depth for highly packed immobilized cells has been reported to be in the range of 50 to 200 μm.

Substrates Transfer to Immobilized Microorganisms

According to P. Gikas and A.G. Livingston (1997), significant substrate concentration gradients may exist for cell immobilized in bioreactor. Cells located close to the nutrient supply are likely to maintain higher quality and activity in comparison to cells located relatively further away, leading to differentiation in the quality/activity of the immobilized cell population. This differentiation is more pronounced if there are starvation regions (practically zero substrate concentration) inside the reactor.

Typical approaches for measuring diffusivities in immobilized cell systems include bead methods, diffusion chambers, and holographic laser inter-ferometry. These methods can be applied to various support materials, but they are time consuming, making it onerous to measure D_eff over a wide range of cell fraction. Due to the mathematical models involved, the deconvolution of diffusivities can be very sensitive to errors in concentration measurements. Mark R. Riley develop a semi-empirical relation used to predict D_eff as a function of D₀, D_c, and Φ. The relation also can be used to extrapolate D_eff measurement from one cell fraction to any other cell fraction. For example, one experimental measurement of D_eff at a known value of Φ can be used to calculate D₀/D_c for a particular system using the equation:

(3)

Once D₀/D_c is known, it can be substituted back in equation (3.4.4) to predict diffusivities for the full range of cell fractions.

(4)

One D_eff measurement at a known Φ was used to calculate D₀/D_c for that particular diffusing species and particular cell type. This D₀/D_c value was used o predict D_eff for the full range of cell fraction (0.0 ≤ Φ ≤1.0). Various value of D₀/D_c have been compiled in table 3 for a variety of immobilized cell systems. These diffusivity ratio for specific systems (i.e. diffusing species, cell type, and gel material) facilitate the prediction of D_eff value for a wide range of operating conditions.

Table 3: Experimental studies of diffusion in immobilized cell systems and their associated values of D₀/D_c calculated:

Cell Type	Immobilization	Solute	D0/Dc
Saccharomycess cerevisiae	Ca-alginate	glucose	1
Baker's yeast	Ca-alginate	glucose	10.6
Ehrlich ascites tumor	agar, collagen	glucose	2.4
Zymomonas mobilis	k-carrageenan, Ca-alginate	glucose	∞
Pseudomonas aeruginosa	Ca-alginate	glucose	2.3
Saccharomycess cerevisiae	Ca-alginate	glucose	2.8
Plant	Ca-alginate	sucrose	∞
Baker's yeast	Ca-alginate	galactose	15.8
Zymomonas mobilis	Ca-alginate	galactose	∞
Baker's yeast	Ca-alginate	lactose	∞
Ehrlich ascites tumor	agar, collagen	lactic acid	6.7
Clostridium butyricum	polyarylamide, agar collagen	hydrogen	3.2
Escherichia coli	natural aggregates	nitrous oxide	3.9
Saccharomycess cerevisiae	fermentation media	oxygen	2.3
Saccharomycess cerevisiae	Ca-alginate, Ba-alginate	oxygen	1
Escherichia coli	fermentation media	oxygen	2.2
Penicillium chrysogenum	fermentation media	oxygen	5.6
Bacillus amilaliquefaciens	Ca-alginate, PVA-SbQ gel	oxygen	1.8
Saccharomycess cerevisiae	Ca-alginate	ethanol	1
Baker's yeast	Ca-alginate	ethanol	∞

For a few systems, calculated diffusivity ratio are very large ( ∞). Such cases obviously represent a lower bound on D_eff/D₀ as a function of Φ. The infinite diffusity ratio corresponds to a diffusing solute that does not enter the cells (i.e. D_c=0), such as observed with galactose and Z.mobilis cells.

Growth and Colony Formation of Immobilized Microorganisms

As pointed out by Hans and Sanaa (1993), immobilized microorganisms differ in their growth rates and show altered morphological forms of colonies. Adsorbed cells form micro- and macrofilms in which the microorganism in the outer region have another morphology than in the inner region. These microfilms often show different colony forms in relation to their density. Thick films have a slimy character, thin film often show the presence of individual microorganisms. These characteristics can be observed with bacteria, yeast, and also with molds. They are caused by differing oxygen concentrations and limited concentrations of nutrients.

By refer to Ghasem Najafpour (1987), a mathematical model for ICR performance may be obtained by applying a mass balance over a differential of the column:

(5)

where ε is the void volume of the packed column (mL), C_A the substrate concentration (g/L), u the bulk fluid velocity (cm/hr), z the axial reactor length (cm), and r_A the rate of substrate transfer to microbial film (g/L-h).

Assuming plug flow and steady-state behavior, eq. (3.4.5) reduces to

(6)

Plug-flow behavior has been shown in this type of reactor by the use of tracer studies.

The reaction rate for simple fermentation systems is normally given by the Monod equation. This model indicates that the specific conversion rate is constant when applied to an immobilized-cell system. If a first-order rate equation for sugar consumption is used, equation (3.4.6) yields:

(7)

Equation (3.4.7) is a linear first-order differential equation in concentration and reactor length. After separation of variables, the equation can be integrated as

(8)

Integration of the above differential equation yields:

(9)

Thus a linear relationship between ln(C_A/C_A0) and the reactor length should exist if the model accurately describes the immobilized-cell reactor.

Immobilized Systems for Ethanol Production

The most significant advantage of immobilized cell systems is the ability to operate with high productivity at dilution rates exceeding the maximum specific growth rate (μ_max) of the microbe. Several theories have been proposed to explain the enhanced fermentation capacity of microorganisms as a result of immobilization. A reduction in the ethanol concentration in the immediate microenvironment of the organism due to the formation of a protective layer or specific adsorption of ethanol by the support may act to minimize end product inhibition. Alternatively, substrate inhibition may be diminished in the case of a gel matrix, if the rate of fermentation meets or exceeds the rate of glucose diffusion to the cell. A third possibility is that alteration of the cell membrane during the process of immobilization provides improved transfer of substrate into and product out of the microbe.

The effect of temperature on the rate of ethanol production is markedly different for free and immobilized systems. Thus while a constant increase in rate is observed with free Saccharomyces cerevisiae as temperature is increased from 25 to 42°C, a maximum occurs at 30°C with cell immobilized in sodium alginate. The lower temperature optimum for immobilized systems may results from diffusional limitations of ethanol within the support matrix. At higher temperature, ethanol production exceeds its rate of diffusion so that accumulation occurs within the beads. The achievement of inhibitory levels then cause the declines observed in the ethanol production rate.

Significant differences are also apparent with regard to the effect of pH on the fermentation rate. The narrow pH optimum characteristic of fee cell system is replaced by an extremely broad range upon immobilization. This effect stems from the gradient pH that exists within the bead.

Table 4: Ethanol Productivity From Immobilized Systems

System	Feed sugar Conc (g/L)	% of Feed Sugar Utilization	Dilution rate (h^-1)	Max. Ethanol Productivity (g/hr.L)
S. Cerevisiae Carrageenan	Glucose 100	86	1.0	43
S. Cerevisiae Ca-alginate	Glucose 127	63	4.6	53.8
S. Cerevisiae Ca-alginate	Molasses 175	83	0.3	21.3
S. Cerevisiae Carrier A	Molasses 197	74	0.35	25
Z. mobilis Ca-alginate	Glucose 150	75	0.85	44
Z. mobilis Ca-alginate	Glucose 100	87	2.4	102
Z. mobilis Carrageenan	Glucose 150	85	0.8	53
Z. mobilis flocculation	Glucose 100			120
Z. mobilis Borosilicate	Glucose 50			85
Z. mobilis Carrageenan- Locust bean gum	Whey-lactose 50	98		178