BIOTECHNOLOGY LETTERS Volume 18 No. 11 (November 1996) pp.1319-1324 Received as revised 19 September

PATTERNS OF TOXICITY BEHAVIOR IN DIFFERENT TYPES

OF MICROBIAL CULTURE

KUO-CHING LIN and CHUNG-YUAN CHEN*

Institute of Environmental Engineering, National Chiao Tung University

75, Po-Ai Street, Hsinchu, Taiwan 30039, Republic of China

Summary. Responses to copper and sodium pentachlorophenate at various nutrient concentrations, up to COD=1500 mg/1, were compared in different types of microbial cultures : Escherichia coli and activated sludge. In the E coli. culture, effective concentration at 50% inhibition varies from 0.745 mg/1 to 11.56 mg/1 (copper) and from 1.963 mg/l to 8.163 mg/1 (sodium pentachlorophenate) when COD concentrations change from 30 mg/1 to 1500 mg/1, respectively. For the activated sludge, however, EC50 remains stable, indicating toxicity is independent of nutrient status. This phenomenon is mainly related to the species composition which determines the correlation coefficient. Results in this study indicate that the influence of the type of microbial cultures is a crucial factor in determining microbial growth dynamics.

INTRODUCTION

Microbial growth is frequently controlled by more than one limiting substance. Both

toxicants and nutrients can play major roles in microbial population dynamics is

important in natural aquatic ecosystems as well as in laboratory toxicity testing. Several

studies have reported that metal toxicity on algae is affected by the phosphate

concentration (Say and Whitton, 1977; Shehata and Whitton, 1982; Chen, 1994). Chen

(1994) also demonstrated that the average tolerance of algal cells decreases with the

concentration of phosphate. A theoretical analysis demonstrates that the correlation

coefficient (p), which measures the linear association between the tolerance (,~) and the

nutrient requirement (S) for microbial cells, significantly influences the combined effects

of the limiting nutrient and the limiting toxicant. EC50 varies with changes in nutrient concentration if full correlation (p = 1 or -1) exists. On the other hand, EC50 remains

constant if p = 0 (Chen, 1989).

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Our earlier work predicted that, for a pure culture of microorganism, full correlation will

probably be observed because all the individuals are genetically similar. It is also

expected that the degree of correlation between Z and S decreases with an increasing

number of species in a microbial culture. Hence, in the case of activated sludge that

contains an enormous variety of microorganisms, no correlation can be found between

and S because most of the individual cells are genetically dissimilar (Chen, 1988; Chen,

1989). Therefore, this study attempts to verify the above theory by comparing the toxic

responses, at various nutrient concentrations, revealed by the two aforementioned types

of microbial culture (i.e. pure and mixed cultures). Such an understanding of the

influence of different types of microbial cultures is also essential to the fundamentals of

microbiology, for example, in growth dynamics.

MATERIALS AND METHODS

Two types of microbial cultures were studied; an activated sludge (mixed culture) and Escherichia coli (pure culture). Activated sludge (AS) with a solids retention time of 10- 12 days was obtained from a local municipal wastewater treatment plant. Samples were concentrated by gravity settling and aerated continuously in the laboratory for about 30 h before testing to ensure that all exogenous substrate was exhausted. Mixed liquor suspended solids (MLSS) was set equal to 8000 mg/l and mixed liquor volatile

suspended solids (MLVSS) was 6400 mg/1. E. coli ATCC 25922 was incubated at 37°C in the nutrient broth with shaking at 100 rpm. After 9 h incubation, it was then harvested (cell suspension optical density is 1.0 absorbance at 600 nm which is approximately

equal to 1.5 × 109 cells/ml) and centrifuged at 4000g for 5 min. After carefully decanting the supernatant, the E. coli settlement was resuspended in aerated deionized-water and the absorption of E. coli suspension in a spectrophotometer at 600 nm was allowed to set at 1.0 absorbance. The activated sludge liquor and E. coli suspensions, were then spiked with different amounts of nutrient broth. The corresponding nutrient concentration was determined by a COD test. Inhibition of the specific oxygen uptake rate (SPOUR) was the response parameter for toxicity testing. Dissolved oxygen (DO) was determined in a 300 ml BOD bottle employing a DO electrode (YSI 59,YSI Corporation). On-line readings were directly stored in a computer to calculate the corresponding OUR values. A

water bath maintained the temperature at 25 °C for AS and 37 °C for E. coli. The

inhibition rate(%) is equal to [1-(B/A)] × 100, where A is the original SPOUR at a specific nutrient concentration and B the SPOUR after spiking the toxicant. Based on the inhibition rates, EC50 was calculated by the probit model (Finney, 1971). The dissolved metal concentrations were determined by filtering the growth medium samples that has been spiked with copper and then analyzing them by atomic absorption spectrophotometery.

The theory applied here is a mathematical model for microbial growth under stress from both a limiting toxicant and a limiting nutrient. Relative activity is defined as:

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Relative activity = B/A 0 = Pr { S => S, Z < Z } (1)

where A 0 is the SPOUR at nutrient saturated condition, S the nutrient concentration and

S the nutrient requirement, Z is the toxicant concentration and Z the toxicant tolerance. and Z" are two random variables that are assumed to follow certain distribution

functions. The parameter p measures the linear association, in a microbial culture,

between these two variables. A detailed description of the above theory can be found in the authors' previous works (Chen and Christensen, 1985; Chen, 1989).

RESULTS AND DISCUSSION

Toxicity of copper and sodium pentachlorophenate

For both E. coli and activated sludge, the maximum SPOUR values were reached at a

COD concentration of 1500 rag/1. Hence, toxicity tests were conducted at COD

concentrations equal to 1500 rag/1 and below. Table 1 presents the EC50s and 95%

confidence intervals for Cu and sodium pentachlorophenate (NaPCP) according to the

degrees of inhibition on activated sludge. The EC50s for copper remained quite similar at

different nutrient concentrations, and were identical to the results obtained by Anderson

et a1.(1988). Neither are the differences in the EC50s based on the dissolved metal

concentrations obvious. Similar observations were made in the case of NaPCP. For both

copper and NaPCP, the 95% confidence intervals at different nutrient concentrations all

overlapped, indicating that these EC50 values were similar in a statistical sense. The

differences in the EC50s are, in fact, deviations due to random sampling. Table 1

suggests that, for a mixed microbial culture such as activated sludge, the EC50 remains

unchanged irrespective of the variations in nutrient concentration.

nutrient level

(as COD(mgtl))

6O

150

300

1500

Table 1. EC50 value and 95% confidence intervals of toxicant at various nutrient

concentrations in activated sludg

Cu 2+

EC50 (mg/l)

6.184(5.510)

5.689(5.365)

6.252(6.164)

6.091(6.080)

95% C. I.

5.231-7.255

4.227-7.285

4.300-8.489

5.156-7.145

:toxicivtesting.

NaPCP

EC50 (mg/1)

37.21

36.56

37.56

39.78

*EC50s in parenthesis are based on dissolved copper concentrations.

C. I.: Confidence interval.

NaPCP: Sodium pentachlorophenate.

95% C. I.

31.43-42.86

30.37-42.50

33.02-42.07

38.49-41.08

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Table 2 lists the results from the E. coli tests. The EC50s for copper varied from 0.745 to

11.6 mg/1 at different nutrient concentrations. The difference between the greatest and the

smallest values of EC50 is about 16 times. For the last four EC50s, the 95% confidence

intervals at each nutrient concentration do not overlap with other intervals. Hence, we

may assert that these EC50s differ statistically at cr = 5% level. Based on the dissolved

metal concentrations, an even more distinct difference (25 times) between the greatest

and the smallest EC50 was apparent. Similarly, EC50 for NaPCP varied from 1.963 to

8.163 mg/1 at various nutrient levels. From their 95% confidence intervals, we can

conclude that the EC50s at COD concentrations equal to 30, 300, and 1500 mg/l,

respectively, significantly differed at a = 5% level. Table 2 clearly reveals that, in a pure

microbial culture, the EC50 is dependent on the nutrient status.

nutrient level

(as COD (m~/1)) 30 150 300 600 1500

Table 2. EC50 value and 95% confidence interval of toxicant at various

nutrient concentrations in E. coli. toxicity test.

Cu 2+ NaPCP

EC50 (mg/l) 0.745(0.472) 0.956(0.722) 1.756(1.670) 4.612(4.567) 11.56(11.55)

95% C. I. 0.575-1.154 0.740-1.192 1.269-2.251 4.055-5.214 9.668-14.49

EC50 (mg/l) 1.963 3.943 4.951 6.073 8.163

*EC50s in parenthesis are dissolved copper concentrations. C. I.: Confidence interval. NaPCP: Sodium pentachlorophenate.

95% C. I. 1.372-3.147 3.097-6.809 3.714-6.717 2.488-7.643 6.905-10.42

To illustrate further the effects of the type of microbial culture on toxicity, Fig. 1 depicts

the inhibition rates of NaPCP observed in the E. coli and activated sludge cultures. The

concentration of NaPCP was maintained at 5 and 40mg/1 for the E. coli and activated

sludge tests, respectively. For the E. coli tests, the inhibition rate varies from 80% to 15%

at different nutrient levels. On the contrary, the observed inhibition rates in the activated

sludge tests remain almost unchanged. Since nutrient broth served in both kinds of test,

it is unlikely that the observed variations in NaPCP toxicity in the E. coli tests were due

to interactions between NaPCP and the nutrient broth. Fig. 2 is a similar illustration with

respect to copper. The inhibition rate for the E. coli tests ranged from 99% to only 1%.

For the activated sludge tests, however, the inhibition rate was between 45% and 50%.

These observations confirm that average tolerance in a pure microbial culture varies with

the nutrient concentration but remains unchanged in a mixed culture such as the activated

sludge.

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100

90

.-. 80

~ 7o ~ 6o ~ 5o

.~ 40

a= 30

20

10

I ................................................ r o A. s test, NaPCP=40 mg/I

L Q E coh test, NaPCP=5 mg/l

30 60 150 300 600 1500

COD (mg/I)

Fig. 1. Inhibition rates of NaPCP at different nutrient concentrations.

100

90

80

6o

g 5o ~ 40 e~ "~ 30

- - 217

10

I"1A. S. test; Cu=5 mg/l

QE. coil test: Cu=2 mg/l

30 60 150 300

COD (mg/l)

600 1500

Fig. 2. Inhibition rates of copper at different nutrient concentrations.

The correlation coefficient p

An analysis of p requires describing the distributions for the random variables Z and S.

The relationship between nutrient broth concentration and SPOUR was fitted by the

Probit model to describe the distribution of nutrient requirement (5). Likewise, the

concentration-response relationship of a toxicant, at saturation nutrient level, defines the

distribution of tolerance (Z). Equation (1) can thus be integrated with an assumed p

value. At a specific nutrient concentration, an EC50 was determined by calculating the

relative activities for various toxicant concentrations. The Z 2 values between the

calculated and observed EC50s were then estimated. The optimum p was indicated by

the minimum Z 2 value. This procedure has been explained in detail in our previous work

(Chen, 1994).

Table 3 summarizes the Z 2 analysis for all four previously discussed cases. The Probit

models, which describe the distributions of Z and S, are set out in the lower half of the

table. For both copper and NaPCP, p = 0 is the optimum condition for the activated

sludge culture. On the other hand, p = 1 is an appropriate description for the E. coli

culture. The above analysis indicates that the number of species in a microbial culture

determines the parameter p. For a pure culture, full correlation (p = 1) is most likely

owing to the genetic similarities between the individual cells. Such similarities, however,

do not exist in the activated sludge culture. The phenomena verified in this study were

identical to the theoretical analysis predicted by our earlier work (Chen, 1989).

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Table 3. X 2 analysis for different p in activated sludge and E. coli toxicity tests

/9 Activated sludge E. coli

Cu NaPCP Cu NaPCP

0 0.0322 a 0.5513 a 32.34 8.692 0.1 0.3409 0.7281 24.40 6.542 0.2 1.240 4.517 21.07 5.445 0.9 25.06 119.1 4.659 0.8429 1.0 26.82 143.6 4.20 a 0.6569 a

(1) Activated sludge S : Y=1.543+1.668 log S

Cu Z : Y=3.881+1.425 log Z

NaPCP Z : Y=2.710+1.431 log Z

(2) E. coli S : Y=0.974+1.640 log S

Cu Z : Y=3.179+1.695 logZ

NaPCP Z : Y=0.880+4.518 log Z

a: minimum X 2 for each set of tests.

The above discussion demonstrates the effects of culture type on toxicity at various nutrient concentrations. The correlation coefficient p , which has been previously ignored and left undefined, has now been given by our work a biological interpretation. Since most toxicity testing protocols are single-species in nature, the effects of the nutrient status on the ECS0 should be taken into account when extrapolating laboratory results for field conditions. We believe that the conclusions drawn from this study are also essential to microbial growth dynamics for multiple toxicity or multiple nutrient limitation: It has been proven that the concentration addition model for multiple toxicity and "Liebig's Law of the Minimum" for multiple nutrient limitation are both related to the condition of p = 1 (Chen and Christensen, 1985; Chen, 1988). These models are, therefore, most probably relevant to single-species cultures because full correlation between S and 7 may exist.

ACKNOWLEDGEMENTS - This research was supported in part by grants from the

National Science Council, Taiwan, Republic of China (NSC 85-2211-E-009-013). The

help of Mr. Cheng-Liang Lu for the experimental work is highly appreciated.

REFERENCES

Anderson, K., Koopman, B. and Bitton, G. (1988). Wat. Res., 22:3,349-353. Chen, C.Y. (1988). Wat. Sci. Technol., 20:11/12, 513-515. Chen, C.Y. (1989). Toxic. Assess., 4, 35-42. Chen, C.Y. (1994). Wat. Res.,28:4, 931-937. Chen, C.Y. and Christensen E.R. (1985). Wat. Res., 19:6, 791-798. Finney, D.J. (1971). Probit Analysis, London: Cambridge University Press. Say, P.J. and Whitton, B.A. (1977). Freshwater Biology, 7, 377-384. Shehata, F.H.A. and Whitton, B.A. (1982). Br. Phycol. J., 17, 5-12.

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