Campylobacter spp., Giardia spp., Cryptosporidium spp., Noroviruses ...

APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Jan. 2004, p. 87–95 0099-2240/04/$08.00⫹0 DOI: 10.1128/AEM.70.1.87–95.2004 Copyright © 2004, American Society for Microbiology. All Rights Reserved.

Vol. 70, No. 1

Campylobacter spp., Giardia spp., Cryptosporidium spp., Noroviruses, and Indicator Organisms in Surface Water in Southwestern Finland, 2000-2001 Ari Ho ¨rman,1,2* Ruska Rimhanen-Finne,1 Leena Maunula,3 Carl-Henrik von Bonsdorff,3 Niina Torvela,3 Annamari Heikinheimo,1 and Marja-Liisa Ha¨nninen1 Department of Food and Environmental Hygiene, Faculty of Veterinary Medicine,1 and Department of Virology and HUCH Laboratory Diagnostics, Division of Virology, Haartman Institute,3 University of Helsinki, Helsinki, and The Finnish Defense Forces Medical School, Lahti,2 Finland Received 9 July 2003/Accepted 18 September 2003

A total of 139 surface water samples from seven lakes and 15 rivers in southwestern Finland were analyzed during five consecutive seasons from autumn 2000 to autumn 2001 for the presence of various enteropathogens (Campylobacter spp., Giardia spp., Cryptosporidium spp., and noroviruses) and fecal indicators (thermotolerant coliforms, Escherichia coli, Clostridium perfringens, and F-RNA bacteriophages) and for physicochemical parameters (turbidity and temperature); this was the first such systematic study. Altogether, 41.0% (57 of 139) of the samples were positive for at least one of the pathogens; 17.3% were positive for Campylobacter spp. (45.8% of the positive samples contained Campylobacter jejuni, 25.0% contained Campylobacter lari, 4.2% contained Campylobacter coli, and 25.0% contained Campylobacter isolates that were not identified), 13.7% were positive for Giardia spp., 10.1% were positive for Cryptosporidium spp., and 9.4% were positive for noroviruses (23.0% of the positive samples contained genogroup I and 77.0% contained genogroup II). The samples were positive for enteropathogens significantly (P < 0.05) less frequently during the winter season than during the other sampling seasons. No significant differences in the prevalence of enteropathogens were found when rivers and lakes were compared. The presence of thermotolerant coliforms, E. coli, and C. perfringens had significant bivariate nonparametric Spearman’s rank order correlation coefficients (P < 0.001) with samples that were positive for one or more of the pathogens analyzed. The absence of these indicators in a logistic regression model was found to have significant predictive value (odds ratios, 1.15 ⴛ 108, 7.57, and 2.74, respectively; P < 0.05) for a sample that was negative for the pathogens analyzed. There were no significant correlations between counts or count levels for thermotolerant coliforms or E. coli or the presence of F-RNA phages and pathogens in the samples analyzed. ing to these monitoring studies coastal rivers tend to have higher counts of thermotolerant coliforms than lakes have, which probably indicates that there is a higher fecal contamination load in rivers. However, monitoring programs have not included data on the prevalence of various enteric pathogens in surface water. Few systematic studies have been undertaken in other countries to determine the simultaneous prevalence of various enteric pathogens in surface water (4, 16, 27, 28, 34). Epidemiological studies of waterborne outbreaks have indicated that the most important waterborne pathogens in Finland are the noroviruses (NVs) (formerly referred to as the Norwalk-like viruses) and campylobacters; 11 of 14 reported waterborne outbreaks that occurred during 1998 and 1999 were caused by these microbes (31). One documented outbreak also occurred when consumption of untreated surface water caused severe campylobacter gastroenteritis in military conscripts during a field exercise (1). Enteric parasites, such as Giardia spp. and Cryptosporidium spp., have not been reported to cause waterborne epidemics in Finland according to the National Infection Register (42), but these parasites are well recognized as organisms that are able to cause severe waterborne enteric infections even at small doses, especially in immunocompromised persons (13, 33). Some data on the occurrence in Finland of Giardia spp. and Cryptosporidium spp. in surface waters are available (37).

Surface freshwater is widely used as a source for drinking water production; the majority of the world’s human population uses surface water as drinking water. In 2001 42% of the drinking water consumed in Finland originated directly from various surface water sources (41). Treated or untreated surface water is also one of the main sources of drinking water under field conditions when there is no sanitary or municipal infrastructure, both for military use and civil organizations and for individual hikers. Historical and present data on raw water quality combined with data on purification capacity play an essential role when water safety plans recommended by the World Health Organization are applied to drinking water production (10, 19, 22). Surface waters are also used a great deal for leisure and recreational activities, and unintended ingestion of microbiologically contaminated water poses a potential health risk (40). Extensively collected and documented monitoring data are available in Finland for the hygienic quality of surface water sources based on counts of fecal indicator microbes, mainly thermotolerant coliforms and Escherichia coli (32, 36). Accord-

* Corresponding author. Mailing address: Department of Food and Environmental Hygiene, Faculty of Veterinary Medicine, University of Helsinki, P.O. Box 57, 00014 Helsinki University, Finland. Phone: 358 (0)40 5560851. Fax: 358 (0)9 19149718. E-mail: [email protected]. 87

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FIG. 1. Geographic locations of surface water sampling sites in southwestern Finland.

In addition to data on the occurrence and prevalence of various enteropathogens, it is crucial to have data on the correlation between fecal indicators and enteric pathogens in surface water. Thermotolerant coliforms, E. coli, fecal enterococci, and Clostridium perfringens are used as indicator organisms worldwide for microbial water hygiene (12, 39). Bacteriophages, such as somatic coliphages, F-RNA bacteriophages, or phages of Bacteroides fragilis, have also been proposed as indicator organisms (9, 35), but data on their prevalence in Finnish surface waters are limited (9). The ecology and environmental survival characteristics of bacterial, viral, and parasitic enteropathogens vary, indicating that probably no single indicator organism can predict the presence of all enteric pathogens. Furthermore, whether there is a true correlation between the indicator organisms generally used and pathogens and to what extent and under which circumstances these organisms can be used as reliable determinants in water hygiene have been discussed previously (11, 12, 26, 43). In this study one of our aims was to investigate simultaneously the occurrence of various enteropathogens belonging to different microbial groups, including Campylobacter spp., Giardia spp., Cryptosporidium spp., and NVs, in diverse types of surface water in southwestern Finland during different consecutive seasons. Our second aim was to analyze the correlation between the pathogens and selected indicator parameters, including counts of thermotolerant coliforms and E. coli, the presence of C. perfringens and F-RNA bacteriophages, and turbidity. MATERIALS AND METHODS Sampling sites and sampling. A total of 139 water samples were collected at 30 different sites (Fig. 1) on five separate sampling occasions within a 2- to 3-week period in consecutive seasons. The sampling sites were selected to include the most important rivers and lakes representing various contamination sources and catchment areas in southwestern and coastal Finland. Primary selection was made on a macro level (lake or river) and on a micro level (sampling site) (20) by using map reconnaissance. The sites included seven lakes and 13 rivers and an additional 10 separate sites in two rivers (5 sites in each river), the Aura River and the Kokema¨ki River. These two rivers were included in the study due to their importance as local drinking water sources and due to the differences in their total flow rates, water volumes, and catchments areas. Exact sampling

points were recorded by using a Garmin global positioning system 12XL (Garmin, Olathe, Kans.) satellite device. The first samples were collected in September and October (autumn) 2000; this was followed by collection of samples in February and March (winter), May (spring), August (summer), and finally October (autumn) 2001. During the first sampling period 19 samples were collected from 19 sites (Aura River and Kokema¨ki River were not included), and during the four subsequent sampling periods the number of samples and sampling sites was increased to 30. The sampling protocol consisted of collecting four separate subsamples at each sampling site at every sampling time; three separate 1-liter samples were used for bacteriological, virological, and physicochemical analyses, and one 10-liter grab sample was used for parasitological analysis. The samples were taken from the nearshore areas of lakes or rivers at depths of 0.5 to 1 m (20 to 30 cm beneath the surface), and sediment that would contaminate the samples was avoided. During the winter sampling was done by collecting the samples with a pump through holes made in the ice cover. The water samples were transported within 24 h after collection to laboratories and were stored cooled (at 5 to 8°C) prior to analysis, which was begun within 24 h. Analyses of E. coli and thermotolerant coliforms. E. coli counts were obtained from 100 ml of a sample by using the Colilert-18/Quanti-Tray 2000 most-probable-number (MPN) test (IDEXX Laboratories, Inc., Westbrook, Maine); the test procedure described by the manufacturer was used. Thermotolerant coliform counts were determined by filtering a 100-ml sample through a 0.45-␮mpore-size cellulose filter (Millipore Corporation, Bedford, Mass.). The filter was then placed on an incubation patch impregnated with liquid m-FC broth with rosolic acid (Millipore). The filters were incubated at 44.5 ⫾ 0.5°C for 24 ⫾ 2 h, and the blue colonies were counted as thermotolerant coliforms. Analysis of C. perfringens. For the C. perfringens analysis 100 ml of a sample was first heat treated in a water bath at 70 ⫾ 2.0°C for 10 min to kill vegetative bacteria and cooled (2). The heated and cooled sample was then filtered through a 0.45-␮m-pore-size cellulose filter (Millipore), and the filter was placed on a Shahidi Ferguson perfringens agar plate (Becton Dickinson Microbiology Systems, Franklin Lakes, N.J.) containing 0.4 mg of D-cycloserine per g. The plate was incubated anaerobically at 44 ⫾ 0.5°C for 24 h. A sample was determined to be C. perfringens positive if typical black colonies were present on the plate, and the colonies were confirmed to be C. perfringens colonies by using the method described in the ISO 6461-2 standard (2). Analysis of Campylobacter spp. A 100-ml sample was filtered through a 0.45␮m-pore-size cellulose filter (Millipore), and the filter was placed in a petri dish filled with 20 ml of liquid Bolton campylobacter enrichment broth without antibiotics (LabM, Bury, Lancashire, United Kingdom). After incubation in a microaerobic atmosphere at 37 ⫾ 1.0°C for 6 h, 0.2 ml of a selective supplement containing cephoperazone, vancomycin, trimethoprim, and cycloheximide (LAB M X131; LabM) was added to the enrichment broth. Incubation was continued microaerobically for a further 24 h at 42 ⫾ 0.5°C. After the selective enrichment phase, a 10-␮l portion of broth was spread onto the surface of a modified CCDA agar plate (Oxoid Ltd., Basingstoke, Hampshire, United Kingdom) and incubated microaerobically at 37 ⫾ 1.0°C for 48 h. The sample was positive for campylobacters if small grayish colonies were detected, if it was oxidase and

VOL. 70, 2004 catalase positive, and if a typical curved cell morphology was observed after Gram staining. A typical colony was inoculated onto blood agar and incubated microaerobically at 42 ⫾ 0.5°C for 24 h. Bacterial isolates were stored at ⫺70°C for further analysis. The cultures were identified to the species level by using catalase, hippurate hydrolase, and indocylacetate hydrolase tests (17). Analysis of NVs and F-RNA bacteriophages. Virological analysis for detection of NVs was performed by reverse transcriptase PCR (29) after concentration of the water samples (15, 25). Briefly, 1,000 ml of water was filtered through a positively charged membrane (AMF-Cuno; Zetapor, Meriden, Conn.) by using a fiberglass prefilter. Possible viruses were eluted from the membrane with 50 mmol of glycine-NaOH (pH 9.5) containing 1% beef extract. Further concentration (to 100 ␮l) was performed with a Centricon-100 microconcentrator (Amicon, Beverley, Mass.). RNA was extracted from concentrated water samples with a phenol-containing reagent (Tripure; Roche Diagnostics, Basel, Switzerland) and was precipitated with 75% ethanol. After a common reverse transcription step, separate PCRs for NV genogroups I and II were performed; PCR amplicons that were 152 and 117 bp long were obtained with primers NVp110 and NVp69 and with primers NVp110 and NI, respectively. The amplified products were confirmed by using a probe panel in a microplate hybridization assay (29). Analysis for the presence of F-RNA bacteriophages was performed as described in the ISO 10705-1 standard (3). The samples were mixed with host strain Salmonella enterica serovar Typhimurium WG49, and they were grown on a semisolid tryptone-yeast extract-glucose-based agar. MS2 was used as a positive control. For exclusion of DNA bacteriophages, samples were also grown in the presence of RNase. Analysis of Giardia spp. and Cryptosporidium spp. For concentration of cysts and oocysts, 10-liter grab samples were filtered through a polycarbonate filter, and the concentrates were further purified by immunomagnetic separation (37). After immunomagnetic separation, each 50-␮l product was divided and used for immunofluorescence assay (IFA) microscopy and PCR. For PCR, the immunobead-oocyst complexes were rinsed twice with phosphate-buffered saline–Tween 20, and the DNA of the parasites was released by repeated freeze-thaw cycles. The amplification reaction mixture (total volume, 50 ␮l) contained 2.5 U of HotStarTaq DNA polymerase, 1⫻ PCR buffer containing 1.5 mmol of MgCl2 per liter and 200 mmol of each deoxynucleoside triphosphate (HotStarTaq Master Mix; Qiagen; Hilden, Germany) per liter, 12.6 pmol of primers cry15 and cry9 (Cryptosporidium spp.), 50 pmol of primers GDH1 and GDH4 (Giardia spp.), and 5 ␮l of the template. The PCR was performed with a thermal cycler (DNA Engine PTC-200; MJ Research, Waltham, Mass.) by using the following temperature cycles: for Cryptosporidium spp., 94°C for 15 min, followed by 30 cycles of denaturation at 94°C for 1 min, annealing at 55°C for 1 min, and extension at 72°C for 1 min and then a final extension at 72°C for 10 min; and for Giardia spp., 94°C for 15 min, followed by 35 cycles of denaturation at 94°C for 1 min, annealing at 55°C for 1 min, and extension at 72°C for 1 min and then a final extension at 72°C for 7 min. During microscopy, cysts and oocysts were detected by direct IFA by using an Aqua-Glo G/C kit (Waterborne, New Orleans, La.). The slides were first screened with an epifluorescence microscope (Nikon type 115) at a magnification of ⫻200, and the particles with green fluorescence were confirmed by using a magnification of ⫻400. Objects that were ovoid or spherical and had a diameter of 4 to 6 ␮m were recorded as Cryptosporidium spp., and particles that were round to oval and had a diameter of 5 to 18 ␮m were recorded as Giardia spp. A sample was determined to be positive if a positive result was obtained either by PCR or by IFA or if both tests were positive. Physicochemical analysis. Temperature, pH, and conductivity were measured with portable devices; temperature was measured with a Delta Ohm HD8601P (Delta Ohm, Padua, Italy), pH was measured with a Eutech Cybernetics pHScanWP2 (Eutech Instruments, Singapore), and conductivity was measured with a HACH model C0150 conductivity meter (HACH Company, Loveland, Colo.) immediately after sampling at the sampling site. Turbidity was measured in the laboratory for each thoroughly stirred sample on the day after sampling by using a Eutech CyberScan WL TB1000 turbimeter (Eutech), and the results were expressed in nephelometric turbidity units. Statistical analyses. All individual results were recorded by using Microsoft Excel 2002 software (Microsoft Corporation, Redmond, Wash.), and a statistical analysis was performed with the Statistical Package for Social Sciences 11.5 for Windows (SPSS Inc., Chicago, Ill.) software. Prevalences were calculated for each microbe analyzed, and arithmetic means and standard deviations were calculated for MPNs of E. coli, turbidity, and temperature separately for each sampling time and type of sampling site (all lakes plus the Kokema¨ki River, the Aura River, and other rivers). Analysis of variance (ANOVA) was used to determine possible significant differences at a P level of ⬍0.05 for prevalences and means for different sampling times and sites. If significant differences were

ORGANISMS IN SURFACE WATER IN FINLAND

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observed, Duncan’s post hoc test was performed to determine which values differed from all other values. All samples were grouped according to the thermotolerant coliform and E. coli counts at four different levels, and the prevalence of enteropathogens and indicator microbes at each level was analyzed by using ANOVA and Duncan’s post hoc test. A nonparametric Spearman rank order correlation coefficient with a twotailed P value was calculated for cross-correlations between different indicator parameters (coliform and thermotolerant coliform counts, MPNs of E. coli, turbidity values, and presence or absence of C. perfringens and F-RNA bacteriophages). Spearman’s correlation coefficient was also computed for bivariate correlations between indicator parameters and pathogen findings. The odds ratio (OR) with a 95% confidence interval was calculated for each sample, and the value was positive for pathogens analyzed according to the outcome for various indicator parameters. All the samples were divided into two groups: pathogen absent or pathogen present (i.e., the sample was either negative for Campylobacter spp., Giardia spp., Cryptosporidium spp., and NVs or was positive for at least one of the pathogens). Pathogen absence was considered a dependent variable in the logistic multivariable regression model. In this model various indicator parameters (i.e., levels of E. coli and thermotolerant coliforms and the presence of C. perfringens and F-RNA bacteriophages) were considered independent variables, and their predictive values for the dependent variable were analyzed by computing the coefficient estimates (B values), P values for the B values, and ORs with 95% confidence intervals from the B values.

RESULTS Enteropathogens. A total of 57 of 139 samples (41.0%) were found to be positive for at least one of the enteropathogens analyzed (Campylobacter spp., Giardia spp., Cryptosporidium spp., or NVs). Of these 57 positive samples, 46 contained one of the pathogens analyzed; two pathogens were isolated from 10 samples, and three pathogens were isolated from one sample. Pathogens were isolated less frequently (3 of 30 samples; 10.0%) during the winter (P ⬍ 0.05) than during the other sampling periods (Table 1). There was not a significant difference (P ⬎ 0.05) in the prevalences of positive samples for pathogens at different types of sampling sites (lakes or the Aura River, the Kokema¨ki River, or other rivers) (Table 2). Only 1 of the 30 individual sampling sites was found to be negative for all enteropathogens studied at all five sampling times. Ten sites were found to be positive at only one sampling time, 10 sites were positive at two sampling times, and nine sites were positive at three sampling times. None of the sampling sites was found to be positive for one or more of the pathogens analyzed at all five sampling times. Campylobacter spp. were isolated from 24 samples (17.3%) and were the most frequently isolated enteropathogens in this study (Table 1). Of 24 campylobacter-positive samples, 11 (45.8%) were found to contain Campylobacter jejuni, 6 (25.0%) were found to contain Campylobacter lari, and 1 (4.2%) was found to contain Campylobacter coli, while 6 (25.0%) of the strains were undetermined Campylobacter spp. More samples were positive for campylobacters in May 2001 (43.3% of the samples were positive) than at other sampling times (P ⬍ 0.05). Lakes and the Aura River were positive for campylobacters significantly (P ⬍ 0.05) more often than the Kokema¨ki River or other rivers (Table 2). NVs were detected in 13 samples (9.4%); 3 of the positive samples contained genogroup I NVs, and 10 of the positive samples contained genogroup II NVs. There were no differences in the prevalence of NVs when sampling times were compared (Table 1), but the Kokema¨ki River was found to be positive for NVs more frequently (P ⬍ 0.05) than the other

41.0 9.4 10.1 13.7 17.3 33.8 31.7 150.3 (433.9) 37.7 (41.4) 10.4 (6.4) 30 139 Total

Mean (standard deviation). b Mean (standard deviation). NTU, nephelometric turbidity units. The P value for the differences between values is 0.020, as determined by ANOVA. c Mean (standard deviation). The P value for the differences between values is 0.351, as determined by ANOVA. d The P value for the differences between values is ⬍0.001, as determined by ANOVA. e The P value for the differences between values is 0.006, as determined by ANOVA. f The P value for the differences between values is 0.008, as determined by ANOVA. g The P value for the differences between values is 0.475, as determined by ANOVA. h Sample was positive for at least one of the following pathogens: Campylobacter spp., Giardia spp., Cryptosporidium spp., or NVs. The P value for the differences between values is ⬍0.001, as determined by ANOVA. i Value is significantly different at the 0.05 (95%) level from other values for individual sampling times in the same column.

19 30 30 30 30 September and October 2000 February and March 2001 May 2001 August 2001 October 2001

a

36.8 10.0i 56.7 60.0 41.0 5.3 10.0 10.0 16.7 3.3 15.8i 0i 0i 23.3i 13.3 5.3 0i 10.0 20.0i 30.0i 21.1 0i 43.3i 23.3 0i 21.1 80.0i 36.7 20.0 6.7i 300.0 (749.6) 212.7 (494.8) 92.8 (219.7) 72.2 (180.7) 128.5 (438.6)

No. of samples

19 30 30 30 30

9.6 (3.4) 0.5 (0.4) 12.3 (1.2) 19.0 (1.2) 10.3 (1.3)

42.4 (42.9)i 36.8 (33.2) 48.3 (49.2)i 16.4 (12.4) 46.2 (51.6)i

57.9i 23.3 60.0i 13.3 13.3

F-RNA phagesd C. perfringensd

% of positive samples

E. coli (MPN/ 100 ml)c Turbidity (NTU)b Temp (°C)a


Sampling time

No. of sampling sites

Indicator parameters

Campylobacter spp.d

Giardia spp.e

Cryptosporidium spp.f

% of samples positive for pathogens

NVsg

Any pathogenh

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TABLE 1. Indicator parameters and proportions of samples positive for various pathogens for 139 surface water samples collected between September 2000 and October 2001 in southwestern Finland according to the sampling time

90

sampling sites (Table 2). NVs were the only pathogens analyzed for which there were significant differences in occurrence among the 30 sampling sites; 2 separate river sites were positive for NVs more frequently (P ⬍ 0.01) than the remaining 28 sites. Giardia spp. were isolated from 19 (13.7%) of the 139 samples, and Cryptosporidium spp. were isolated from 14 (10.1%) of the 139 samples (Tables 1 and 2). Both Giardia spp. and Cryptosporidium spp. were found more frequently during the summer of 2001 and less frequently during the winter of 2001 than at the other sampling times (P ⬍ 0.05). No significant differences between the proportions of positive samples at different types of sampling sites were detected. Results for indicator microbes. The MPNs of E. coli were below the detection limit of the test used (one microbe per 100 ml) for 13 samples (9.3%), while 110 samples (79.1%) had MPNs of E. coli of 100 CFU per 100 ml or less (Table 3). Only five samples (3.6%) had MPNs of ⬎1,000 CFU per 100 ml. The MPNs of E. coli varied widely for individual samples; thus, there were no significant differences at a P level of 0.05 in mean MPNs when sampling times (Table 1) or sites (Table 2) were compared. However, the MPNs tended to be higher in the Aura River and most other rivers than in the lakes and the Kokema¨ki River (Table 2). The samples are arranged according to thermotolerant coliform counts in Table 4. A total of 44 samples (31.7%) were positive for C. perfringens, and 47 samples (33.8%) were positive for F-RNA bacteriophages (Tables 1 and 2). C. perfringens was isolated most frequently during the autumn of 2000 and spring of 2001 (P ⬍ 0.05). No sample from the Kokema¨ki River was found to be positive for C. perfringens. There were no differences (P ⬎ 0.05) in the occurrence of F-RNA bacteriophages when sampling sites were compared, but phages were isolated more often during the winter of 2001 and less frequently during the autumn of 2001 (P ⬍ 0.05). Physicochemical results. The turbidity varied between 1.2 and 222.0 nephelometric turbidity units, and the variations both between sampling times (Table 1) and between types of sampling site (Table 2) were significant (P ⬍ 0.05). The temperature varied during the study period from 0.1 to 22.0°C, but the variation within each sampling season was very limited (Table 1). The conductivity (mean, 143.4 ␮S/cm2; standard deviation, 65.9 ␮S/cm2; minimum, 64.0 ␮S/cm2; maximum, 398.0 ␮S/cm2) and pH (mean, 7.51; standard deviation, 0.44; minimum, 6.4; maximum, 9.5) did not vary significantly (P ⬎ 0.05) for different sampling times or for different types of sampling site. Correlation between indicator parameters and enteropathogens. The indicator parameters used in this study (turbidity, thermotolerant coliform counts, MPNs of E. coli, and presence of C. perfringens) showed significant cross-correlations with each other (correlation coefficients, 0.30 to 0.86; P ⬍ 0.05). However, the presence of F-RNA phages showed no significant correlation (P ⬎ 0.05) with any other parameter except turbidity and MPNs of E. coli, for which there were low but significant levels of correlation (correlation coefficients, 0.30 and 0.21; P ⬍ 0.05). The presence of any of the pathogens analyzed did not correlate significantly with the presence of other pathogens (P ⬎ 0.05 for Spearman correlation coefficients [data not shown]).

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TABLE 2. Indicator parameters and proportions of samples positive for various pathogens for 139 surface water samples collected between September 2000 and October 2001 in southwestern Finland according to the sampling site Indicator parameters Sampling site

Lakes Riversk Aura River Kokema¨ki River Total

No. of samples

No. of sampling sites

Turbidity (NTU)a

E. coli count (MPN/100 ml)b

% of samples positive for pathogens

% of positive samples C. perfringensc

F-RNA phagesd

Campylobacter spp.e

Giardia spp.f

Cryptosporidium spp.g

NVsh

Any pathogeni

35 58 26 20

7 13 5 5

15.8 (14.6) 75.2 (407.9) 43.7 (43.4)i 232.6 (548.8) j 76.2 (43.5) 148.0 (275.9) 8.4 (4.0) 45.9 (151.9)

25.7 41.4 42.3 0j

20.0 41.4 42.3 25.0

20.0j 13.8 34.6j 0

14.3 8.6 15.4 25.0

11.4 13.8 7.7 0

2.9 10.3 3.8 25.0j

34.3 39.7 50.0 45.0

139

30

37.7 (41.4)

31.7

33.8

17.3

13.7

10.1

9.4

41.0

150.3 (433.9)

a

Mean (standard deviation). NTU, nephelometric turbidity units. The P value for the differences between values is ⬍0.001, as determined by ANOVA. Mean (standard deviation). The P value for the differences between values is 0.278, as determined by ANOVA. The P value for the differences between values is 0.003, as determined by ANOVA. d The P value for the differences between values is 0.112, as determined by ANOVA. e The P value for the differences between values is 0.010, as determined by ANOVA. f The P value for the differences between values is 0.381, as determined by ANOVA. g The P value for the differences between values is 0.431, as determined by ANOVA. h The P value for the differences between values is 0.044, as determined by ANOVA. i Sample was positive for at least one of the following pathogens: Campylobacter spp., Giardia spp., Cryptosporidium spp., or NVs. The P value for the observed differences between values is 0.590, as determined by ANOVA. j Value is significantly different at the 0.05 (95%) level from other values for individual types of sampling sites in the same column. k Aura River and Kokema¨ki River data are not included. b c

Significant (P ⬍ 0.05) bivariate nonparametric Spearman rank order correlation coefficients and ORs for various indicator parameters and pathogens in samples are shown in Table 5. Based on these bivariate correlations, four variables (levels of E. coli and thermotolerant coliform counts, absence of C. perfringens, and absence of F-RNA bacteriophages) were selected for use in a multivariate logistic regression model (Table 6) in which the absence of E. coli, thermotolerant coliforms, and C. perfringens had a significant (P ⬍ 0.05) predictive value (ORs, 1.15 ⫻ 108, 7.57, and 2.74, respectively) for a sample being negative for any of the pathogens analyzed. DISCUSSION Our results showed that all the enteropathogens analyzed can be detected in surface water from lakes and rivers located

in southwestern Finland. This was the first systematic study done in Finland in which enteropathogens representing different microbial groups (NVs as a model for enteric viruses, campylobacters as a model for enteric bacterial pathogens, and Giardia spp. and Cryptosporidium spp. as models for resistant protozoan parasites) were analyzed for diverse surface water sites during several consecutive seasons. The point prevalences of the various enteropathogens in our study, as well in all biological and environmental studies, are dependent on sampling time and site, but findings can serve as rough general estimates for the prevalences in surface water as a whole and can provide qualitative data for risk assessment. The results showed that there was some tendency for seasonal variation: during the winter the pathogens were detected less frequently than during the spring, summer, or autumn. This pattern was observed especially for the occurrence of Campylobacter spp.,

TABLE 3. Proportions of surface water samples positive for indicators and pathogens at various levels of E. coli in samples % of positive samples E. coli count (MPN/100 ml)

⬍1 1–10 10.1–100 100.1–1,000 ⬎1,000 Total a

No. of samples (%)

Indicators

Pathogens

C. perfringensa

F-RNA phagesb

Campylobacter spp.c

Giardia spp.d

Cryptosporidium spp.e

NVsf

Any pathogeng

13 (9.3) 55 (39.6) 42 (30.2) 24 (17.3) 5 (3.6)

0h 18.2h 35.7h 58.3h 100.0h

23.1 23.6 38.1 54.2 40.0

0 21.8 21.4 12.5 0

0 20.0 14.3 4.2 20.0

0 12.7 16.7 0 0

0 9.1 4.8 16.7 40.0

0h 47.3 47.6 33.3 60.0

139 (100.0)

31.7

33.8

17.3

13.7

10.1

9.4

41.0

The P value for the differences between values is ⬍0.001, as determined by ANOVA. The P value for the differences between values is 0.088, as determined by ANOVA. The P value for the differences between values is 0.249, as determined by ANOVA. d The P value for the differences between values is 0.207, as determined by ANOVA. e The P value for the differences between values is 0.129, as determined by ANOVA. f The P value for the differences between values is 0.050, as determined by ANOVA. g Sample was positive for at least one of the following pathogens: Campylobacter spp., Giardia spp., Cryptosporidium spp., or NVs. The P value for the differences between values is 0.016, as determined by ANOVA. h Value is significantly different at the 0.05 (95%) level from other values for E. coli count ranges in the same column. b c

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TABLE 4. Proportions of surface water samples positive for indicators and pathogens at various levels of thermotolerant coliforms in samples % of positive samples Thermotolerant coliform count (CFU/100 ml)

No. of samples (%)

⬍1 1–20 20.1–200 200.1–2,000 ⬎2,000 Total

Indicators

Pathogens

C. perfringensa

F-RNA phagesb

Campylobacter spp.c

Giardia spp.d

Cryptosporidium spp.e

NVsf

Any pathogeng

11 (7.9) 45 (32.4) 48 (34.5) 30 (21.6) 5 (3.6)

0h 15.6 41.7 43.3 80.0h

27.3 28.9 33.3 46.7 20.0

0 20.0 22.9 13.3 0

0 11.1 14.6 16.7 40.0

0 11.1 16.7 3.3 0

0 13.3 0 20.0h 20.0h

0h 40.0 43.8 50.1 60.0

139 (100.0)

31.7

33.8

17.3

13.7

10.1

9.4

41.0

a

The P value for the differences between values is ⬍0.001, as determined by ANOVA. The P value for the differences between values is 0.511, as determined by ANOVA. The P value for the differences between values is 0.296, as determined by ANOVA. d The P value for the differences between values is 0.273, as determined by ANOVA. e The P value for the differences between values is 0.231, as determined by ANOVA. f The P value for the differences between values is 0.019, as determined by ANOVA. g Sample was positive for at least one of the following pathogens: Campylobacter spp., Giardia spp., Cryptosporidium spp., or NVs. The P value for the differences between values is 0.047, as determined by ANOVA. h Value is significantly different at the 0.05 (95%) level from other values for thermotolerant coliform count ranges in the same column. b c

Giardia spp., and Cryptosporidium spp., and the pattern was not affected when we excluded the samples obtained during the first sampling period, during which fewer samples were collected than at other sampling times, from the statistical analysis. The major dissimilating factors between seasons in watersheds in Finland and regions with similar climatic conditions are temperature, ice cover, and solar radiation. Low temperatures in water during the winter and high solar radiation during the summer are known to have effects on the survival and recovery of Campylobacter spp. In studies done in Norway (6, 21) and Finland (23), campylobacters in natural water exhibited seasonal patterns, and the number of positive samples was highest in the winter and lowest in the summer. C. jejuni and C. coli survive in cold water (at temperatures below 10°C) much longer than they survive in water at temperatures higher than 18°C (23, 24). A confounding factor in the assessment of campylobacter seasonality in water is birds, which are carriers of C. jejuni, C. lari, and C. coli (17, 44) and contaminate watershed areas where they live. Birds were probably the cause of the rather high numbers of campylobacter-positive samples in August 2001, even when the temperature of the water was ⬎18°C in areas where positive samples were collected. There have been few studies on the possible seasonality of the intestinal parasites Giardia spp. and Cryptosporidium spp. in surface waters. Lower numbers of samples positive for these parasites during the cold winter months than during other seasons have been found in some studies (45). In one study the highest frequencies of samples positive for Giardia spp. and Cryptosporidium spp. were found during the autumn and winter in surface waters affected by agricultural discharges due to heavy rains (5), but no clear seasonality has been found in some other studies (38). Possible seasonal or time-related variation in the occurrence of various groups of enteric pathogens in surface water appears to be dependent on the source of contamination and the conditions facilitating the discharge of contaminants into surface water. If the major sources are sewage plants that treat human

wastes, seasonal patterns similar to those observed for human infections for a particular pathogen are detected in effluents and downstream water samples (25). If the watershed is contaminated by discharges resulting from agricultural runoff, the highest numbers of zoonotic enteric pathogens are found during the pasture season after snowmelt, floods, and heavy rainfalls (5). Even though most of the NV infections in Finland occur (according to the Finnish Infection Register) in the winter and early spring (42), no clear winter peak in the number of samples positive for NVs was detected in our study, and positive samples were detected in all seasons. We obtained no evidence that enteric pathogens are more frequent in certain types of surface water in Finland. However, we did observe a trend for higher E. coli counts in the Aura River and other rivers than in lakes and the Kokema¨ki River, confirming the results of previous monitoring studies (32, 36). There was also a tendency for higher turbidity values in rivers (except the Kokema¨ki River) than in lakes; this result reflects the general appearance of coastal rivers with high loads of inorganic material and clay in the water combined with relatively low flow rates. The sampling sites were selected to represent diverse types of lakes and rivers with variable contamination sources and catchment areas. However, the statistical analysis did not reveal any significant correlation between the enteropathogens analyzed as a whole and any particular type of surface water sampling site; enteropathogens were found to the same extent at all sampling sites. This may have resulted from the fact that all sites were in relatively densely populated areas of Finland subject to discharges from human activities, as well from agriculture. The occurrence of the various pathogens did not correlate significantly with traditionally used fecal indicator parameters (counts or count levels for E. coli or thermotolerant coliforms per 100 ml) or turbidity. In some studies a significant correlation has been found between the level of thermotolerant coliforms and the number of samples positive for certain pathogens (4, 34). However, a poor correlation similar to that shown in the present study has also been demonstrated elsewhere (8,

VOL. 70, 2004

Turbidity r (P)a

0.22 (0.009)f

r (P)

0.27 (0.001)f

Presence of E. colib

OR (95% CI)

1.83 (1.56–2.14)

r (P)

⫺0.17 (0.043)g 0.20 (0.018)g

E. coli levelc

OR (95% CI)

0.87 (0.81–0.94) 3.84 (1.18–12.50)

Thermotolerant coliform level r (P)d

0.20 (0.020)g

OR (95% CI)

1.80 (1.54–2.11)

Presence of thermotolerant coliformsb

r (P)

0.24 (0.004)f

OR (95% CI)

4.08 (1.27–13.14)

Thermotolerant coliform levele

r (P)

0.21 (0.012)g 0.34 (⬍0.001)f

r (P)

2.26 (1.09–4.67)

6.21 (2.40–16.06)

OR (95% CI)

Presence of C. perfringensb

0.19 (0.027)g

r (P)

0.20 (0.04–0.89)

OR (95% CI)

Presence of F-RNA phagesb

⫺0.20 (0.021)g

TABLE 5. Analysis of significant (P ⬍ 0.05) bivariate Spearman rank order correlation coefficients with two-tailed P values and ORs with 95% confidence intervals for correlation between various indicator parameters and pathogens

Pathogen

Campylobacter sp.

Cryptosporidium spp.

Giardia spp.

NVs

Any pathogenh

a r, Spearman rank order correlation coefficient; P, two-tailed P value. b Not detected versus detected in 100 ml. CI, confidence interval. c ⱕ100 MPN/100 ml versus ⬎100 MPN/100 ml. d The levels were ⬍1, 1 to 20, 20.1 to 200, 200.1 to 2,000, and ⬎2,000 CFU/100 ml. e ⱕ200 CFU/100 ml versus ⬎200 CFU/100 ml. f The correlation is significant at the 0.01 (99%) level. The correlation is significant at the 0.05 (95%) level. Sample was positive for at least one of the following pathogens: Campylobacter spp., Giardia spp., Cryptosporidium spp., or NVs.

g

h

14, 26, 43). The presence or absence of a correlation between fecal indicators and pathogens could reflect the occasional appearance of enteropathogens in surface waters and the different rates of survival and recovery of the pathogens compared with those of fecal indicators. One possible factor affecting the low correlation could also be different microbial densities in the original contamination sources, and therefore, the failure to detect pathogens was due to sampling volumes that were too small (14, 17). For detection of Giardia spp. and Cryptosporidium spp. 10-liter samples were used, for NVs 1liter samples were used, and for Campylobacter spp., E. coli, and thermotolerant coliforms 100-ml samples were used. However, detection of E. coli or thermotolerant coliforms in a sample had significant predictive value for a sample being positive for one or more of the pathogens analyzed. In multivariable analysis detection of no E. coli or thermotolerant coliforms in a 100-ml sample had significant positive predictive value for a sample being negative for all of the pathogens analyzed. Therefore, the presence or absence of E. coli and thermotolerant coliforms appears to be a better predictor for the occurrence of enteropathogens than a certain level of these microbes is. There was a positive correlation between the presence of C. perfringens and a sample being positive for one or more of the pathogens analyzed, and detection of no C. perfringens had positive predictive value for a sample being negative for all of the pathogens analyzed. However, a considerable number of samples that did not contain C. perfringens were positive for some of the pathogens analyzed and vice versa, which decreased the usefulness of C. perfringens as a reliable indicator for enteropathogens. The spores of C. perfringens persist for a long time in water; this persistence is considered to be much longer than that of most enteropathogenic bacteria (7). Cysts of Giardia spp. and oocysts of Cryptosporidium spp (30) are known for their capacity to survive for several months in water (25), and it has been suggested that C. perfringens is a useful indicator for these parasites (35). In our hands, C. perfringens was not a reliable indicator for the presence of cysts or oocysts, suggesting that C. perfringens is likewise not a suitable indicator for the protozoan parasites Giardia spp. and Cryptosporidium spp. The presence of F-RNA bacteriophages could not be linked with the presence of NVs or any other enteric pathogen in a sample, and therefore, these phages cannot serve as reliable indicator organisms. There were some previous studies on the correlation of F-RNA phages with NVs which suggested that bacteriophages are suitable indicators for enteric viruses (11, 18). The present study provided valuable qualitative data for assessing microbial risks in surface waters in Finland. The occurrence of enteropathogens in surface waters is linked directly to possible contamination sources, while environmental conditions affect only the survival of these microbes in water. The presence of traditionally used fecal indicators, including thermotolerant coliforms and E. coli, has significant predictive value for the presence of the enteropathogens studied, but no significant correlation was found between a certain level of indicators and the presence of pathogens. Microbial monitoring of raw water by using only fecal indicator organisms is not sufficient for assessment of the occurrence of a particular enteropathogen.


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TABLE 6. Multivariate analysis by logistic multiple regression model with no pathogen detected as the dependent variablea Model-fitting information Model or variable

Models Intercept only Final Variables Intercept Level of E. coli NDb 1–10 MPN/100 ml 10.1–100 MPN/100 ml ⬎100 MPN/100 ml Level of thermotolerant coliforms ND 1–20 CFU/100 ml 20.1–200 CFU/100 ml ⬎200 CFU/100 ml Presence of C. perfringens (ND) Presence of F-RNA bacteriophages (ND)

Parameter estimates

⫺2 Log likelihood

Chi square

df

P

92.546 64.423

28.123

10

0.002

Exp (B) (95% confidence interval)

B

⫺0.48

SE for B

P

1.008

0.636

18.56 ⫺2.24 ⫺1.43 0.67

1.15 0.11 0.24 1.96

⫻ 108 (1.15 ⫻ 108–1.15 ⫻ 108) (0.01–3.69) (0.01–6.59) (0.07–52.42)

⬍0.001 1.81 1.69 1.68

⬍0.001 0.216 0.398 0.69

2.02 1.97 1.61 ⫺0.23 1.00 0.19

7.57 7.16 5.02 0.80 2.74 1.21

(7.57–7.57) (0.24–214.06) (0.19–133.65) (0.03–19.70) (1.12–6.69) (0.54–2.74)

⬍0.001 1.73 1.68 1.64 0.46 0.42

⬍0.001 0.26 0.336 0.889 0.027 0.646

a When no pathogen was detected, the sample was determined to be negative for each of the following pathogens: Campylobacter spp., Giardia spp., Cryptosporidium spp., and NVs. b ND, not detected.

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