presence-absence (P-A) test and by the membrane filter (MF) method. ... of the P-A test with those of other coliform detection ..... growth in the different media.
Vol. 52, No. 3
APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Sept. 1986, p. 439-443
0099-2240/86/090439-05$02.00/0 Copyright C 1986, American Society for Microbiology
Comparison of Clark's Presence-Absence Test and the Membrane Filter Method for Coliform Detection in Potable Water Samples WESLEY 0. PIPES,* HARVEY A. MINNIGH, BLAKE MOYER, AND MARLEEN A. TROY Department of Civil Engineering and Environmental Studies Institute, Drexel University, Philadelphia, Pennsylvania 19104 Received 24 October 1985/Accepted 28 May 1986
A total of 2,601 water samples from six different water systems were tested for coliform bacteria by Clark's presence-absence (P-A) test and by the membrane filter (MF) method. There was no significant difference in the fraction of samples positive for coliform bacteria for any of the systems tested. It was concluded that the two tests are equivalent for monitoring purposes. However, 152 samples were positive for coliform bacteria by the MF method but negative by the P-A test, and 132 samples were positive by the P-A test but negative by the MF method. Many of these differences for individual samples can be explained by random dispersion of bacteria in subsamples when the coliform density is low. However, 15 samples had MF counts greater than 3 and gave negative P-A results. The only apparent explanation for most of these results is that coliform bacteria were present in the P-A test bottles but did not produce acid and gas. Two other studies have reported more samples positive by Clark's P-A test than by the MF method.
colony counts of 0. When coliforms are found, the colony counts are usually small (6). Thus, for the comparison of different methods, it is important to evaluate the methods in term of their sensitivity for detection of coliforms at low densities. Standridge and Delfino (7), in a study which included measuring coliform detection at low densities, postulated that when a sample had a low coliform density and was well mixed before a portion was removed for analysis, the probability of some number, x, of coliform bacteria in the portion was given by the Poisson equation
J. A. Clark has described a presence-absence (P-A) test for detection of coliform bacteria in samples of potable water (4, 5). This test uses a single fermentation bottle, and the sample volume can be either 100 or 50 ml. When a positive result is obtained, there is no information about the number of coliforms in the sample. Clark's P-A test has been in use in Ontario for over 15 years, and he has compared the results of the P-A test with those of other coliform detection methods for thousands of samples (5). Proposals for the National Revised Primary Drinking Water Regulations are under consideration by the U.S. Environmental Protection Agency (Notice of Proposed Rulemaking, Federal Register 48:45502, 1983). It is likely that in the revised regulations, a presence-absence concept will be adopted for the microbiological maximum contaminant level. This concept bases judgments about microbiological water quality on the number of samples examined each month which have coliform bacteria present rather than on some parameter related to the concentration of coliforms. The presence-absence concept for monitoring and regulation is different from Clark's P-A test, but the adoption of the former could permit the use of the P-A test in the United States. At present two procedures are approved by the U.S. Environmental Protection Agency for bacteriological examination of water samples; these are the membrane filter (MF) method and the fermentation tube technique (2). Either of these procedures will give an estimate of the coliform density in a water sample when a positive result is obtained. If the presence-absence concept of monitoring is adopted for the revised regulations, it is expected that the MF and fermentation tube methods will continue to be used for monitoring water systems. However, Clark's P-A test may also be approved for use and could be adopted by many utilities because of its relative simplicity and lower cost per sample. Routine monitoring of drinking water distribution systems for coliform bacteria by the MF method of analysis usually results in the majority of the water samples yielding coliform *
P{x}
=
e-\XIx!,
where is the actual coliform density in the water sample. Thus, if a water sample has a volume of 1,000 ml and there are 10 coliform bacteria present, the probability of no coliforms in a 100-ml sample is 0.368, the probability of 1 coliform per 100 ml is 0.368, the probability of 2 per 100 ml is 0.184, and so forth. We have undertaken a comparison of the MF procedure and Clark's P-A test for coliform detection in water samples (4, 5) and have found the Poisson model proposed by Standridge and Delfino (7) to be useful for interpreting the results. This paper deals with the problem of comparing coliform detection by the two tests at both high and low coliform densities. MATERIALS AND METHODS
Clark's P-A test was performed according to the procedure which he described (4, 5) but with the medium specified in the 16th edition of Standard Methods (1). The P-A bottles were incubated at 35 + 0.5°C for up to 5 days and examined daily for growth (turbidity), acid production, and gas production. The production of acid and gas within 48 h was considered a positive presumptive coliform reaction. All P-A bottles showing evidence of acid and gas production were subjected to the verification procedure of being transferred to brillant green bile broth. Most of the P-A bottles showing acid but no gas production were also verified, but less than 2% of those bottles had coliforms present.
Corresponding author. 439
APPL. ENVIRON. MICROBIOL.
PIPES ET AL.
440
TABLE 1. Water systems sampled System System
SR
~Population served 550
Raw
of SmlnpeidNo. Sampling period samples
Data set
water
gallonsb/day)(101
Avg pumpage
Treatmenta
source
SR/1 SR/2
10-28 July 1983 3-25 June 1984
213 213
Well
C
70
WH
3,600
WH/1 WH/2
25 July-22 Aug 1983 15 Oct.-10 Nov. 1983
205 204
Well
C
300
BL
2,700
BL/1 BL/2
20 Aug.-18 Sept. 1983 25 Sept.-19 Oct. 1983
229 225
Well
C, F
200
BG
750
BG/1
10-30 July 1984 13-28 May 1985
215 214
Well
C
100
BG/2
FF/1
3-20 Aug 1984 14 Sept.-3 Oct 1984
225 224
Well
None
FF/2
FV/1 FV/2
25 Aug.-7 Sept 1984 17 April-9 May 1985
210
Surface
C, S, F
224
FF FV
90
280
9 20
S, Sedimentation; F, filtration; C, chlorination. One gallon is ca. 3.79 liters.
a
b
MF tests were performed according to the procedures in Standard Methods (1) and were incubated at 35 + 0.5°C on m-Endo LES agar for 22 to 24 h. All typical coliform colonies on a filter were picked for confirmation if five or fewer were found. When the presumptive coliform colony count was more than five, at least five representative colonies were selected for confirmation. Confirmation was accepted as growth plus gas production in both lauryl tryptose
and brilliant green bile broths. Standard plate counts were also made using the pour plate method described in Standard Methods (1). Both field and laboratory tests were used to compare the MF and P-A procedures. For field sampling, six water distribution systems were selected for sampling (Table 1). Samples were collected from private residences throughout each system. Water was allowed to run from the tap for at
TABLE 2. Comparison of coliform detection by P-A and MF methods No. of samples
System (1)
SR
Sampling
pe(r2i)od T(o3t)al (2) (2) (3)
Negative (4)
MF
Fraction positive P-A
MF) positive ~~positive (6) ~~~ ~~(5) ~ positive
Z for
positive
(7)
for no. MF positive, vs
MF
(9)
PA (10)
positive,b MF
0.99 1.12
0.005 0.206 0.106
0.000 0.164 0.082
3 and negative P-A results, there are 132 samples listed on the first line of Table 3 which gave positive P-A test results but negative MF results. There is no independent information which can be used to estimate the coliform densities in these samples. Some of these results almost certainly are the consequence of random dispersion of coliform bacteria in a
well-mixed sample. However, it is not possible to rule out the possibility that there was interference with coliform colony development on the membrane filter, resulting in a false-negative result. Another possible explanation of the results detailed in Tables 3 and 4 is sampling from some distribution other than the Poisson. If the coliform bacteria in the water sample were not randomly dispersed but had a contagious distribution, the results could be easily explained without postulating a difference in the two methods. A laboratory study of the Poisson model proposed by Standbridge and Delfino (7) was undertaken. Data from this study are presented in Table 5. The results of the laboratory experiments agree very well with the results predicted by the Poisson probability model and suggest that this model provided an adequate explanation of the difference in the results for individual samples with low coliform densities. However, somne of the observed differences for individual samples (Table 4) are not explained by the Poisson probability model and may be the result of differences in coliform growth in the different media. The overall implication of these results is that comparisons of different techniques for determining and enumerating bacteria in water need to be based on large numbers of samples and, if possible, replicate analyses of individual samples. Such a procedure will tend to adduce different methodological reactions to varying sample conditions, and no likely alternative can fully test a procedure under all conditions. Furthermore, for samples at the current limit of detection or for sets of discrete samples with mean densities near 1 per sampling unit, the Poisson probability model provides a robust test of model reliability. ACKNOWLEDGMENT This research was supported in part by a cooperative agreement, CR-810713, from the Environmental Monitoring and Support Laboratory, U.S. Environmental Protection Agency. LITERATURE CITED 1. American Public Health Association. 1984. Standard methods for the examination of water and wastewater, 16th ed. American Public Health Association, New York. 2. Bordner, R., J. Winter, and P. Scarpino. 1978. Microbiological methods for monitoring the environment-water and wastes, EPA-600/8-78-017. Environmental Monitoring and Support Laboratory, U.S. Environmental Protection Agency, Cincinnati, Ohio. 3. Christian, R. R., and W. 0. Pipes. 1983. Frequency distribution of coliforms in water distribution systems. Appl. Environ. Microbiol. 45:603-609. 4. Clark, J. A. 1969. The detection of various bacteria indicative of water pollution by a presence-absence (P-A) procedure. Can. J. Microbiol. 15:771-780.
VOL. 52, 1986 5.
Clark, J. A. 1980. The influence of increasing numbers of nonindicator organisms by the membrane filter and presenceabsence tests. Can. J. Microbiol. 26:827-832.
5a.Jacobs, N. J., W. L. Zeigler, F. C. Reed, T. A. Stukel, and E. W. Rice. 1986. Comparison of membrane filter, multiple-fermentation-tube, and presence-absence techniques for detecting total
coliforms in small community water systems. Appl. Environ. Microbiol. 51:1007-1012.
COMPARISON OF COLIFORM DETECTION METHODS
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6. Pipes, W. O., and R. R. Christian. 1984. Estimation of mean coliform densities of water distribution systems. J. Am. Water Works Assoc. 76:60-64. 7. Standridge, J. H., and J. J. Delfino. 1983. Effect of ambient temperature storage on potable water coliform population estimates. Appl. Environ. Microbiol. 46:1113-1117. 8. Zar, J. H. 1974. Biostatistical analysis. Prentice Hall, Englewood Cliffs, N.J.
