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Journal of Environmental Quality 31:1273-1278 (2002)
© 2002 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

TECHNICAL REPORTS
Surface Water Quality

Geographic Variability of Escherichia coli Ribotypes from Animals in Idaho and Georgia

Peter G. Hartel*,a, Jacob D. Summera, Jennifer L. Hilla, J. Victoria Collinsa, James A. Entryb and William I. Segarsa

a Dep. of Crop and Soil Sciences, 3111 Plant Sciences, Univ. of Georgia, Athens, GA 30602-7272
b USDA–ARS, Northwest Irrigation and Soils Research Lab., 3793 North 3600 East, Kimberly, ID 83341

* Corresponding author (pghartel{at}arches.uga.edu)

Received for publication July 16, 2001.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Several genotypic methods have been developed for determining the host origin of fecal bacteria in contaminated waters. Some of these methods rely on a host origin database to identify environmental isolates. It is not well understood to what degree these host origin isolates are geographically variable (i.e., cosmopolitan or endemic). This is important because a geographically limited host origin database may or may not be universally applicable. The objective of our study was to use one genotypic method, ribotyping, to determine the geographic variability of the fecal bacterium, Escherichia coli, from one location in Idaho and three locations in Georgia for cattle (Bos taurus), horse (Equus caballus), swine (Sus scrofa), and chicken (Gallus gallus domesticus). A total of 568 fecal E. coli isolates from Kimberly, ID (125 isolates), Athens, GA (210 isolates), Brunswick, GA (102 isolates), and Tifton, GA (131 isolates), yielded 213 ribotypes. The percentage of ribotype sharing within an animal species increased with decreased distance between geographic locations for cattle and horses, but not for swine and chicken. When the E. coli ribotypes among the four host species were compared at one location, the percent of unshared ribotypes was 86, 89, 81, and 79% for Kimberly, Athens, Brunswick, and Tifton, respectively. These data suggest that there is good ribotype separation among host animal species at each location. The ability to match environmental isolates to a host origin database may depend on a large number of environmental and host origin isolates that ideally are not geographically separated.

Abbreviations: ATCC, American Type Culture Collection • DIG-labeled, digoxigenin-labeled • rRNA, ribosomal RNA • UPGMA, unweighted pair–group method using arithmetic averages


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
ONE OF THE MOST frequently cited water quality impairments is the presence of fecal bacteria in drinking and recreational waters. The sources of these bacteria are the feces of warm-blooded animals, typically from malfunctioning septic drainfields, animal wastes applied to land, and wildlife defecating in the water. Because a good correlation exists between the presence of pathogenic and nonpathogenic intestinal bacteria (e.g., Geldreich, 1970), certain nonpathogenic bacteria are often used as indicator bacteria. The most common indicator bacteria are the fecal coliforms and fecal streptococci (Clesceri et al., 1998), although some researchers advocate the use of other indicator bacteria (e.g., Bacteriodes spp.; Fiksdal et al., 1985).

In recent years, several phenotypic and genotypic methods have been developed for determining the host origin of fecal bacteria in contaminated waters, a technique commonly referred to as microbial source tracking or bacterial source tracking. All of these methods are based on the assumption that specific markers or strains of bacteria can be identified as originating from specific animal species (e.g., Amor et al., 2000). Although there are reports of using fatty acid methyl ester analysis and serotyping for microbial source tracking (e.g., Parveen et al., 2001), most of the recent research on phenotypic methods has concentrated on multiple antibiotic resistance (Hagedorn et al., 1999; Harwood et al., 2000; Parveen et al., 1997; Wiggins, 1996; Wiggins et al., 1999). Multiple antibiotic resistance appears to work well, but its stability and reproducibility has been questioned because antibiotic use is dynamic and antibiotic resistance genes are typically encoded on plasmids that may be lost or gained depending on environmental conditions (Freter, 1984). Some genotypic methods may circumvent this problem. For example, genotypic methods based on 16S ribosomal RNA (rRNA) are considered highly stable because the section of DNA encoding for this RNA is highly conserved (Grimont and Grimont, 1986). Genotypic methods include ribotyping (e.g., Carson et al., 2001), pulsed field gel electrophoresis (e.g., Kariuki et al., 1999), and various PCR methods (e.g., Dombek et al., 2000; Farnleitner et al., 2000).

Most genotypic studies for microbial source tracking have been conducted with the fecal coliform, Escherichia coli. Samadpour and Chechowitz (1995) matched 421 of 589 E. coli ribotype patterns (71%) from Little Soos Creek (in Washington State) to cattle, deer, dog, duck, horse, human, llama, swine, and poultry. Subsequent studies in several U.S. national parks and recreational areas also linked E. coli to various animal hosts (Berghoff, 1998; Farag and Goldstein, 1998; Tippets, 1999). Pulsed field gel electrophoresis identified the host origin of E. coli isolates in oyster beds (Simmons et al., 1995) and coastal swimming areas (Simmons and Herbein, 1998), and ribotyping identified differences between human and nonhuman sources of E. coli under conditions of a saltwater to freshwater gradient (Parveen et al., 1999). Bernhard and Field (2000a)(2000b) used a PCR assay to discriminate between human and cow fecal contamination of water based on differences in genes encoding for 16S rRNA from the Bacteroides–Prevotella group. This method has yet to be extensively field-tested.

Regardless of whether a microbial source tracking method is phenotypically or genotypically based, some of these methods depend on a host origin database to identify the environmental isolates. One major question about using a host origin database of E. coli subspecies is how geographically variable these fecal subspecies may be, that is, how cosmopolitan (found in more than one geographic location) or endemic (limited to one geographic location) they may be (Staley and Gosink, 1999). If regional variation does occur, then a geographically limited database may not be universally applicable.

Little research has been conducted on the geography of fecal bacteria. Research with E. coli strains from humans and zoo animals suggests that the strains are nearly clonal and not geographically limited (Miller and Hartl, 1986). However, Souza et al. (1999) analyzed a collection of 202 E. coli strains obtained from 81 mammalian species in Australia and the Americas, and found that geographic origin was one of the most important factors for differentiating the E. coli strains. They attributed the differences between their research and earlier research to selection of a wider variety of host animal species, particularly wild animals, and to a greater geographic isolation of the strains.

We conducted a study to determine the geographic variability of E. coli isolates from Idaho and three locations in Georgia for four host animal species, cattle (Bos taurus), horse (Equus caballus), swine (Sus scrofa), and chicken (Gallus gallus domesticus). Ribotyping was the method selected because it has excellent reproducibility, good discriminatory power, excellent ease of interpretation, and ease of performance (Farber, 1996).


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Selection and Identification of E. coli Isolates
Isolates of E. coli were obtained directly from the animal feces of cattle, horse, and swine within a two-county area of Kimberly, ID, and Athens, Brunswick, and Tifton, GA (Fig. 1) . Because Georgia is ranked first in the USA for broiler production (Georgia Agricultural Statistics Service, 1999), E. coli isolates were also obtained from chickens in the three Georgia locations. To maximize ribotype diversity, between two and five E. coli isolates were obtained from the feces of each individual animal and, whenever possible, at least five animals of each species were tested at each location. Within each of the four sampling locations, no two animals of the same species were sampled at one place. Fresh feces were sampled with a culture swab containing Cary–Blair medium (Becton Dickinson, Sparks, MD). Swabs were kept on ice for a maximum of 24 h before streaking on 5-cm petri dishes containing mTEC medium (Difco Laboratories, Sparks, MD). Plates were incubated submerged in a water bath at 44.5 ± 0.2°C for 24 h according to standard methods (Clesceri et al., 1998). Yellow isolates were randomly selected, streaked onto tryptic soy agar (Difco), and incubated at 35°C for 24 h. The streaking was repeated twice to ensure the purity of each isolate. Each isolate was inoculated into a 24-multiwell tissue culture plate containing separate 1-mL slants of Simmons citrate and urea agar (both Difco). Three bacterial species from the American Type Culture Collection (ATCC; Manassas, VA) were used as controls: Escherichia coli ATCC no. 11775 (citrate negative, urea hydrolysis negative), Klebsiella pneumoniae ATCC no. 13883 (citrate positive, urea hydrolysis positive), and Enterobacter aerogenes ATCC no. 13048 (citrate positive, urea hydrolysis negative). Isolates that were both citrate-negative on Simmons citrate agar and urea hydrolysis-negative on urea agar were subjected to an oxidase test (MacFaddin, 1976). Isolates that were oxidase negative were considered E. coli and kept for long-term storage. To do this, a loopful of each isolate (approximately 40 mg) was removed from a tryptic soy agar plate, placed in a cryoprotectant mixture of saline–phosphate (NaCl, 8.5 g L-1, K2HPO4, 0.65 g L-1; KH2PO4, 0.35 g L-1; pH 7.0; 700 µL), glycerol (100 µL), and dimethyl sulfoxide (100 µL), and stored at -70°C.



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  		Fig. 1. Location of the four sampling sites in Georgia and Idaho. The distance among the three Georgia locations is shown; the distance between Kimberly, ID, and the three Georgia locations is approximately 2900 km. At each location, isolates of Escherichia coli were obtained from cattle, horse, and swine. Because of the importance of broiler production in Georgia, chickens were also sampled at the three locations in Georgia.

 
DNA Extraction and Quantification
Isolates of E. coli were streaked on tryptic soy agar and incubated at 35°C for 24 h. A single clone was inoculated into 10 mL of Luria-Bertani broth (pH 7.5; Sambrook et al., 1989) contained in a 16 by 150 mm test tube and secured flat on a rotating shaker at 75 rpm at 35°C. After 18 h, a 2.0-mL sample was removed and the DNA extracted with a commercial kit (Qiagen DNeasy, Qiagen, Valencia, CA). A portion of the DNA was mixed with Hoechst Dye no. 33258 (Amersham Pharmacia Biotech, Piscataway, NJ) according to the manufacturer's directions, and the DNA was quantified with a fluorometer (DynaQuant DQ200, Amersham Pharmacia Biotech). DNA from E. coli strain B (Sigma Chemical Co., St. Louis, MO) was the standard.

Ribotyping of E. coli Isolates
A standard ribotyping protocol was followed, similar to that of Parveen et al. (1999). Briefly, two 1-µg samples of DNA from each isolate were each separately digested overnight with the restriction enzymes EcoRI and PvuII. The digested DNA was stained and was loaded into a 1% agarose gel. The gel was electrophoresed at 58 V for 3 h using a horizontal gel system. Digoxigenin-labeled (DIG-labeled) Marker III (Roche Molecular Biochemicals, Indianapolis, IN) was the molecular weight marker and occupied every fifth lane of the gel. Control lanes contained no DNA (control) and DNA from E. coli ATCC no. 11775. DNA was transferred by Southern blotting to a nylon membrane with a vacuum blotting system and the DNA on the membrane was crosslinked with UV light. Following a 2-h prehybridization at 42°C, the membrane was hybridized at the same temperature overnight to DIG-labeled cDNA from E. coli total ribosomal RNA. Membranes were prepared for chemiluminescence by a series of washing steps before a chemiluminescent substrate for alkaline phosphatase was added. Membranes were placed in a FluorChem 8000 imager (Alpha Innotech, San Leandro, CA) and images saved as TIFF files. The TIFF files were imported into GelCompar II (Applied Maths, Kortrijk, Belgium) for analysis. Typically, gels showed 9 to 11 bands for EcoRI and 11 to 13 bands for PvuII digestion, and this was considered sufficient for good discrimination among ribotypes. DNA fragments <1375 base pairs were ignored because they were often indistinct. Lanes were normalized within the gel with the molecular weight marker, and variations among the gels were assessed with the E. coli ATCC no. 11775 strain. Optimization (maximum percentage shift allowed between two different patterns for the patterns to still be considered a match) and tolerance (maximum percentage shift allowed between two bands on different patterns for the bands to still be considered a match) were each set at 1.00%. The normalized banding patterns for both enzymes were stacked with EcoRI on the top and PvuII on the bottom to create one combined ribotype pattern for each isolate. Similarity indices were determined using Dice's coincidence index (Dice, 1945) and the distance between clusters calculated using the unweighted pair–group method using arithmetic averages (UPGMA). The banding pattern of the control E. coli ATCC no. 11775 strain varied from gel to gel, and a similarity index of 90.0% was required for all the banding patterns to be considered the same ribotype. Based on this variability, the banding patterns of all other isolates had to have a similarity index of >=90.0% to be considered the same ribotype.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
A total of 568 E. coli isolates, including those from Kimberly, ID (125 isolates), Athens, GA (210 isolates), Brunswick, GA (102 isolates), and Tifton, GA (131 isolates), were ribotyped. The isolates came from cattle (234 isolates; 82 ribotypes), horse (120 isolates; 41 ribotypes), swine (149 isolates; 52 ribotypes), and chicken (65 isolates; 38 ribotypes). The isolates yielded a total of 213 ribotypes (based on a 90% similarity index) for an isolate/ribotype ratio of 2.7:1.

When ribotypes of E. coli isolates from cattle in Kimberly, ID, were compared with ribotypes of E. coli isolates from cattle in the Georgia locations of Athens, Brunswick, and Tifton (all approximately 2900 km from Kimberly), the percentage of shared ribotypes was low (0–5%; Table 1) . The percentage of isolates sharing the same ribotypes was also low (0–2%). When the distance was reduced and the ribotypes of E. coli isolates from cattle in Athens, Brunswick, and Tifton were compared with each other, the percentage sharing increased (9–19%). A similar percentage increase (38–48%) was also observed for the number of isolates sharing the same ribotypes.


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  		Table 1. Ribotype sharing for one animal species between two locations. The distance between sampling locations, the total number of isolates at each location, the number and percentage shared ribotypes of the total ribotypes, and the number and percentage of isolates sharing the same ribotypes over the total number of isolates for cattle, horse, and swine at four sampling sites in Georgia and Idaho are given in order of decreasing distance apart. Chickens were only sampled in Georgia.

 
When ribotypes of E. coli isolates from horses in Kimberly, ID, were compared with similar isolates from horses in Athens, Brunswick, and Tifton, GA, the percentage of shared ribotypes was low (5–10%) and similar to that of cattle. The percentage of isolates sharing the same ribotypes between Kimberly and Brunswick, and between Kimberly and Tifton, was also low (3–8%). However, the percentage of isolates sharing the same ribotypes between Kimberly and Athens was 27% (24 of 89 isolates). When the ribotypes of E. coli isolates from horses at all Georgia locations were compared with each other, the percentage of ribotype sharing was 0% between Athens and Brunswick (350 km apart), 8% between Athens and Tifton (260 km apart), and 20% between Tifton and Brunswick (175 km apart). Therefore, the ribotype sharing increased with decreased distance apart. The same relationship was also observed for the number of isolates sharing the same ribotypes (0–52%). Thus, depending on the scale, a decrease in distance between two locations resulted in an increase in ribotype sharing for both cattle and horses.

When ribotypes of E. coli isolates from swine in Kimberly, ID, were compared with similar isolates from swine in Athens, Brunswick, and Tifton, GA, the percentage of shared ribotypes was 0% between Kimberly and Athens, but 14% between Kimberly and Brunswick, and 12% between and Kimberly and Tifton. The percentage of isolates sharing the same ribotypes varied between 0 and 32%. Surprisingly, the percentage of shared ribotypes did not increase with decreasing distance for the three locations in Georgia and remained low (0–7%) for all three locations, as did the percentage of isolates sharing the same ribotype (0–19%).

When ribotypes of E. coli isolates from chicken were compared among the Georgia locations, the percentage of shared ribotypes was low (0–6%). With the exception of the comparison between Athens and Brunswick, the percentage of isolates sharing the same ribotypes was also low (0–9%). The percentage of isolates sharing the same ribotypes was 26% between Athens and Brunswick. Thus, unlike cattle and horses, a decrease in distance between two locations did not result in an increase in ribotype sharing for either swine or chicken.

The number and percent of shared and unshared ribotypes among different combinations of cattle, horse, swine, and chicken at each location (Kimberly, ID, or Athens, Brunswick, and Tifton, GA) were also determined (Table 2) . The vast majority of ribotypes among cattle, horse, swine, and chicken at the four locations was unshared. The percent of unshared ribotypes for the four host animal species at Kimberly, Athens, Brunswick, and Tifton was 86, 89, 81, and 79%, respectively. Only cattle–horse ribotypes were consistently shared at all locations; otherwise all other animal combinations were shared at only one or two locations. Regardless, the percent sharing between or among animals was always <=8%.


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  		Table 2. Unshared and shared ribotypes for all animal species at each location. The number and percent of unshared and shared ribotypes among cattle, horse, swine, and chicken at each location (Kimberly, ID, or Athens, Brunswick, Tifton, GA) are given. Chickens were only sampled in Georgia. Percent is based on the grand total number of ribotypes, and due to rounding off, percent totals do not equal exactly 100%.

 
Although the vast majority of ribotypes among cattle, horse, swine, and chicken at one location were unshared, this was not the case for the number and percentage of E. coli isolates with shared and unshared ribotypes among different combinations of cattle, horse, swine, and chicken at Kimberly, ID, and Athens, Brunswick, and Tifton, GA (Table 3) . The percentage of isolates comprising unshared ribotypes at Kimberly, Athens, Brunswick, and Tifton was 62, 57, 51, and 34%, respectively. It was possible for one shared ribotype to account for many isolates. For example, the percentage of isolates sharing the same ribotype for a cattle–horse–swine combination in Tifton was 48%, but this only represents 2 of 38 ribotypes (5%; Table 2).


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  		Table 3. Number of isolates with unshared and shared ribotypes for all animal species at each location. The number and percent of E. coli isolates with unshared and shared ribotypes among different combinations of cattle, horse, swine, and chicken at Kimberly, ID, and Athens, Brunswick, and Tifton, GA, are given. Chickens were only sampled in Georgia. Percent is based on the grand total number of isolates, and due to rounding off, percent totals do not equal exactly 100%.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
Depending on the scale, there was a relationship between the number of ribotypes shared between two locations and their distance apart for cattle and horses, but not for swine and chicken. Thus, for ribotypes of E. coli from cattle, the percentage sharing was higher (9–19%) for locations closer together (Athens, Brunswick, and Tifton; maximum distance 350 km apart) than for locations farther apart (0–5%; Kimberly and the three Georgia locations; 2900 km apart). In the case of horses, the distance between Athens and Brunswick (350 km) was still too far and no ribotype sharing was observed; it was not until the distance was reduced to 260 km (between Athens and Tifton) that the ribotype sharing (8%) and isolates sharing the same ribotype (32%) increased. However, for ribotypes of E. coli from swine and chicken, this relationship was not observed. Thus, for ribotypes of E. coli from swine, the percentage sharing was no better between locations close together (0–7%; Athens, Brunswick, and Tifton) than for locations far apart (0–14%; Kimberly and the three Georgia locations). Chicken isolates were only obtained from Georgia, but ribotype matching remained low between Tifton and Brunswick (6%; 175 km apart) compared with matching between Athens and Brunswick (3%; 350 km apart). Reasons why this variability occurred is probably due to the distance, sample size, or both. In our study, the minimum distance between the sampling sites was 175 km. This distance was likely too far apart to obtain a high degree of sharing for one host species. Buchan et al. (2001) noted that that the distance between the host source and environmental isolates may have contributed to the poor matching in their study (only 2 matches for 51 environmental isolates). Furthermore, it may be that our sampling size was too small, particularly for chicken. Our isolate/ribotype ratio was 2.7:1 (568 E. coli isolates yielding 213 ribotypes) and this was similar to the 1.7:1 isolate/ribotype ratio (179 total E. coli isolates yielding 102 ribotypes) observed by Parveen et al. (1999). Therefore, the data suggest that a good host origin database for E. coli would contain a large number of isolates obtained from host sources within a 175-km radius. However, future research should probably focus on developing a host origin database within a watershed rather than an arbitrary area.

There was excellent ribotype separation among the four host animal species, with 79 to 89% of all ribotypes being unshared at each location. These results agree with Souza et al. (1999), who suggest that E. coli strains from a wide range of animal hosts from different regions of the world are organized in an ecotypic structure where adaptation to the host plays an important role in the population structure. Nevertheless, all animal species shared ribotypes. In particular, cattle and horses shared ribotypes at all locations. This may be because of similar diet and habitat. The percentage sharing was always <=8% and this is consistent with the maximal 9.5% of PCR DNA fingerprint sharing among cows, chicken, and swine (Dombek et al., 2000).

It is important to note that the number of ribotypes observed here was dependent on the similarity index cutoff. There is a proportional relationship between the similarity cutoff and the number of ribotypes. A low similarity cutoff would yield fewer ribotypes and a higher percentage of sharing than a high similarity cutoff. Here the cutoff was based on the intergel E. coli ATCC no. 11775 control, which established that banding patterns in our study had to be >=90% similar to be considered the same ribotype.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
Ribotyping showed that geographic variability existed for E. coli isolates between one location in Idaho and three locations in Georgia for cattle, horse, swine, and chicken. Decreased distance increased ribotyping sharing for cattle and horse, but not for swine and chicken. Excellent separation among the E. coli ribotypes existed for each of the host animal species, with a minimal amount of ribotype sharing among the four species. This suggests, assuming that the host origin database is comprised of a large number of isolates, ribotyping has good promise to discriminate among host animal species at one location. However, the ability of a database to identify environmental isolates when the host origin isolates are from another geographic location varies. Our results suggest that some E. coli subspecies are cosmopolitan, whereas others are endemic, and this may vary from one host animal species to another. Therefore, researchers should be cautious about the universal use of a host origin database developed for a limited geographic region.

Ribotyping had advantages of excellent reproducibility and discriminatory power. However, the method was slow, expensive, and laborious. As this and other similar methods for identifying fecal contamination are adopted for application, automation may solve these disadvantages.


   ACKNOWLEDGMENTS
 
We thank Adrienne L. Funk, Sheryl Ver Wey, and Andrea L. Wheeler for their technical assistance. We thank Dan Thomas for financial support of Jennifer Hill. This research was partially funded by grants from the U.S. Geological Survey, Georgia Environmental Protection Division, and the Georgia Water Resources Institute.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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