Journal of Biorechnolog?: 5 (1987) 227-231 Usevier

227

JBT 00248

Short Communication

Protein and cell volume distributions during the production of beta-galactosidase in batch

cultures of Kluyveromyces lactis

Bianca Maria Ran& Danilo Porro. Concetta Compagno and Enzo Martegani

Dipnrrinlento di Fisiologia e Biochimica Generali, Se:ione di Biochimica Contparam !?a Celoria 3. Milano, Ita&

(Receivd 20 November 19S6: accepted 27 January 1987)

summary

The yeast Kllqreronyces lacks grown in lactose accumulates /3-galactosidase in a growth associated manner and a maximum of enzyme activity is expressed during a short period between late exponential and early stationary phase.

Segregated parameters like cell volume distribution or protein distribution are sensitive enough to monitor changes of the population structure during different growth phases. In this paper we show the correlation between these distributions and the maximum of enzyme productivity. and we propose that these parameters may be conveniently utilized for monitoring the production of the enzyme in batch cultures.

&Galactosidase. Klyveronyces lactis; Protein distribution; Cell size distribution: Flow-cytometry

The /3-galactosidase (E.C.3.2.1.23) is used as an industrial enzyme in the dairy industry as it allows modification or utilization of products containing lactose (Richmond et al.. 1981). This enzyme is usually obtained from yeasts such as Klqwerornyces lactis, K. marsianrrr, K. fragilis (Richmond et al., 1981) that have an

Correspondence ro: Prof. B.M. Ranzi. Dipartimento di Fisiologia e Biochimica Generali, Via Celoria 26 5B. 20133 Milano. Italy.

0168-1656/87/$03.50 0 1987 Elsevier Science Publishers B.V. (Biomedical Division)

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intracellular fl-galactosidase induced by lactose and related compounds (Dickson and Markin, 1980). The enzyme is continuously synthesized in induced cultures and, in batch operations,’ the maximum yield is obtained at the beginning of the stationary phase of growth, after which the yield of the enzyme decreases (Dickson and Markin, 1980; Holmberg et al., 1984).

To maximize the yield it is necessary to monitor continuously the enzyme formation during the process or to have a mode1 able to predict the optima1 end-point of growth. Holmberg and colleagues (1984) have developed a dynamic mode1 that takes in account many process variables. Using this model, combined with a growth mode1 based on exhaust gas analysis, they tried to estimate the enzyme production indirectly. However the mode1 was not accurate enough for monitoring and control purposes.

In previous reports from our laboratory it has been shown that segregated parameter analysis, and in particular cell volume distribution obtained by Coulter Counter and protein distribution obtained by flow-cytometry, give relevant informa- tions on the growth dynamics and the heterogeneity of budding yeast populations (Alberghina et al., 1983; Ranzi et al., 1986). Protein and cell volume distributions are strongly influenced by growth rate, nutritional conditions (Ranzi et al., 1986) and subtle changes in growth metabolism. They may be linked to enzyme produc- tion and could be identified by a segregated parameter analysis, as recently shown for the production of poly-fl-hydroxybutyrate in bacteria1 cultures (Srienc et al., 1984).

An example of a batch growth experiment is shown in Fig. la, in which Kluyueromyces lads CBS 2360 was grown aerobically at 30°C in YNB-lactose medium (Yeast Nitrogen Base 1.38, lactose 2%). The specific activity of P-galac- tosidase determined according to Miller (1972), remains low (between 3-4 U per lo6 cells) during the exponential phase of growth. It then increases rapidly reaching a maximum at the early stationary phase in a range of 15-20 U per lo6 cells. After that it decreases again as the cell population continues to progress into the stationary phase. During this late growth condition, production of ethanol is observed (Holmberg et al., 1984). This appears to be related to the highest specific activity of /3-galactosidase. However, it reaches its maximum 1 or 2 h after the peak of enzyme production. Therefore, ethanol concentration cannot be a satisfactory parameter for enzyme production monitoring.

As expected cell volume and protein distributions were strongly affected by the growth conditions. They showed continuous changes parallel to changes of physio- logical conditions of the yeast cells and with the fi-galactosidase specific activity. Typical protein and cell volume distributions obtained during exponential growth in YNB-lactose medium are shown in Fig. lb (panels 1, la). These distributions begin to change during late exponential growth and then continue to change parallel to modifications of P-galactosidase concentrations suggesting a possible correlation between the structure of cell population and productivity (Fig. lb, panels 2-5, 2a-5a).

The comparison of different distributions acquired in several independent experi- ments shows that there is an identifiable protein and cell volume distribution related

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TIME(H)

CELL VOLUME b 5

CELL PROTEIN

Fig. 1. a. Increase of cell number and accumulation of ethanol and &galactosidase during batch growth of K/uyueromyces locfis CBS 2360 in YNB-lactose medium. Cell number was determined with a Coulter Counter ZBI (Ranzi et al., 1986). B-Galactosidase was determined according to Miller (1972) and ethanol according to Bemt and Gutman (1974). b. Cell volume and protein distributions of K. lacris at different times (indicated by arrows) during the batch growth in YNB-lactose medium. The maximum of fl-galactosidase activity was observed after 21 h of growth. Cell volume distributions were obtained by a Coulter Counter ZBI (70 pm orifice) linked to a Coulter Channelyzer C-1000. protein distributions by a FACS IV cytoffuorometer (Ranzi et al., 1986).

to the growth phase that gives the maximum yield of P-galactosidase. A &i-square analysis, done between a “reference” distribution and any other given distribution, is a simple way for qualitative comparison of the two distributions (Ranzi et al., 1986). The &i-square analysis was performed between the cell volume distribution measured relative to the maximum of P-galactosidase specific activity and the cell volume distributions acquired in other independent experiments. As shown in Fig. 2 a minimum value is obtained which coincides with the peak of fi-galactosidase activity. In contrast statistical parameters of the distributions like the mean and the

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X2

10 000

I,:;

1000

500

+- TIME (HI

Fig. 2. %-square values (Daniel, 1978) of cell volume distributions obtained by comparing the cell volume distribution observed in correspondence with the maximum of P-galactosidase production, with the cell volume distribution acquired at different times in an independent experiment. The maximum of enzyme activity was at 21 h.

coefficient of variation do not appear to be significant for monitoring purposes (data not shown).

In conclusion our data indicate that it is possible to utilize segregated parameters like cell volume distribution or protein distribution to monitor the production of specific products in yeast populations. Volume distributions appear to change in a way superimposable to protein distribution and are equally satisfactory for the monitoring purposes. We have tested this possibility in cultures of K lads actively producing P-galactosidase. However, in principle this approach could be extended to optimize the production of other interesting enzymes or metabolites in batch cultures.

Acknowledgement

This research was supported by CNR grant no. 85.01276.

References

Alberghina, L., Mariani, L., Martegani, E. and Vanoni, M. (1983) Analysis of protein distribution in budding yeast. Biotechnol. Bioeng. 25, 1295-1310.

Bernt, E. and Gutmann, I. (1974) Ethanol. Determination with alcohol dehydrogenase and NAD. Bergmeyer Methods Enzymatic Analysis 1, Verlag-Chemie, Weinheim. 1499-1502.

Daniel, W.W. (1978) Biostatistics: a foundation for the analysis in the health sciences. John Wiley & Sons, New York.

Dickson, R.C. and Markin, J.S. (1980) Physiological studies of beta-galactosidase induction in K. lacfis. J. Bacterial. 142, 777-785.

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Holmberg, A., Ojamo, H., Perttula, M. and Ranta, J. (1984) Utilization of models in the prediction and optimization of yeast beta-galactosidase production. Third European Congress on Biotechnology, Verlag-Chemie, Weinheim, 1, 699-704.

Miller, J.H. (1972) Experiment in molecular genetics. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, pp. 352-359.

Ranzi, B.M., Compagno, C. and Martegani, E. (1986) Analysis of protein and cell volume distribution in glucose-limited continuous cultures of budding yeast. Biotechnol. Bioeng. 28, 185-190.

Richmond, M.E., Gray, J.I. and Stine. C.M. (1981) /3-Galactosidase: Review of recent research related to technological application, nutritional concerns and immobilization. J. Dairy Sci. 64, 1759-1771.

Srienc, F., Arnold, B. and Bailey, J.E. (1984) Characterization of intracellular accumulation of poly-b-hy- droxybutyrate (PHB) in individual cells of Alculigenes eurrophus H16 by flow cytometry. Biotechnol. Bioeng. 26, 982-987.