Previous Article | Next Article 
Applied and Environmental Microbiology, April 2001, p. 1503-1507, Vol. 67, No. 4
0099-2240/01/$04.00+0 DOI: 10.1128/AEM.67.4.1503-1507.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
Identification of Fecal Escherichia coli
from Humans and Animals by Ribotyping
C. Andrew
Carson,1,*
Brian L.
Shear,1
Mark R.
Ellersieck,2 and
Amha
Asfaw2
Department of Veterinary
Pathobiology1 and Agricultural
Experiment Station Statisticians,2 University of
Missouri, Columbia, Missouri 65211
Received 16 August 2000/Accepted 16 January 2001
 |
ABSTRACT |
Fecal pollution of water resources is an environmental problem of
increasing importance. Identification of individual host sources of
fecal Escherichia coli, such as humans, pets, production animals, and wild animals, is prerequisite to formulation of
remediation plans. Ribotyping has been used to distinguish fecal
E. coli of human origin from pooled fecal E. coli isolates of nonhuman origin. We have extended application of
this technique to distinguishing fecal E. coli ribotype
patterns from human and seven individual nonhuman hosts. Classification
accuracy was best when the analysis was limited to three host sources.
Application of this technique to identification of host sources of
fecal coliforms in water could assist in formulation of pollution
reduction plans.
| |
INTRODUCTION |
Fecal pollution of water resources
is a problem of increasing worldwide concern (4, 15).
Human population growth, inadequate sewage systems, and management of
animal waste (especially related to concentrated animal feeding
operations) are some of the issues associated with maintenance of
supplies of clean water (17). Counts of commensal coliform
bacteria have traditionally been used to indicate the potential
presence of pathogenic microbes of intestinal origin (1).
Total coliform and fecal coliform numbers (1) are useful
for estimating fecal pollution levels but give no indication of the
specific sources of microbial pollution, such as humans, production
animals, pets, or migratory birds. Examples of methods which have been
used as indicators of host sources include phage susceptibility
(20) and the ratio of fecal coliforms to streptococci
(5). Such indirect measurements are based on unstable
parameters and may thereby lead to erroneous conclusions
(11). More recently, DNA fingerprinting techniques such as
ribotyping (11), pulsed-field gel electrophoresis
(9), PCR of repetitive intergenic sequences
(3), and 16S ribosomal DNA length heterogeneity PCR with
terminal restriction fragment length polymorphism (2) have
been described as promising for discriminating between fecal-origin
bacteria from humans and animals. Multiple antibiotic resistance
phenotype has been used to distinguish between human and nonhuman
sources of Escherichia coli (7, 10, 11, 19) and
streptococci (6, 18), but genetic instability or changes
in antibiotic use can alter the resistance profiles obtained.
Ribotyping has been compared to multiple antibiotic resistance
profiles, and both approaches were reportedly complementary in
discriminating between human and nonhuman (collective) sources of fecal
pollution (11). Ribotyping has since become a popular approach (personal communications) to the problem of differentiating between fecal E. coli pollution from humans and, in
particular, that from animals and birds. We describe here the use of
ribotyping for the identification of E. coli cultured from
feces of humans, cattle, swine, horses, chickens, turkeys, dogs, and
migratory geese.
| |
MATERIALS AND METHODS |
Fecal E. coli.
Table
1 presents the host sources of feces, the
numbers of individuals sampled, and the geographic regions from which
samples were collected. E. coli isolates of human origin
were isolated directly from anal swabs. Feces of beef cattle, dairy
cattle, swine, and horses served as source material for isolates from these species. Composite collections were also made from the excreta of
chickens, turkeys, and migratory geese. Samples were incubated overnight in lactose broth at 37°C (Difco Laboratories, Sparks, Md.)
and streaked on mEndo (Les) agar (Difco Laboratories). Colonies presenting a gold metallic sheen were transferred to mFC (Difco Laboratories) and cultured overnight at 44.5°C to select for fecal E. coli. Colonies were further characterized as E. coli by subculture on MacConkey-MUG (Difco Laboratories). Pink
colonies which fluoresced under UV light were transferred to brain
heart infusion (BHI; Difco Laboratories) plates. Individual E. coli isolates were finally confirmed biochemically by growth on
Kligler Iron Agar, Simmons Citrate Agar, Methyl Red/VP, and Indol with
1% tryptose (all from Difco Laboratories). A total of 287 isolates
were examined, including 40 human, 39 cattle, 44 pig, 37 horse, 29 dog,
23 chicken, 26 turkey, and 49 goose isolates.
DNA extraction.
Fecal E. coli isolates were grown
in BHI broth (Difco Laboratories) and DNA extracted by using The Easy
DNA Kit (Invitrogen, Carlsbad, Calif.) according to manufacturer's
instructions. DNA concentration was measured spectrophotometrically,
and 2.5 µg was digested with HindIII (New England
Biolabs, Beverly, Mass.) according to the manufacturer's instructions.
Fragments were separated in 1% agarose gels in TBE buffer (0.09 M
Tris-borate, 0.002 M EDTA) using 30 mV for 16 h.
Southern blot analysis.
Gels were depurinated in 0.25 N HCl
for 15 min, rinsed twice with deionized water, denatured in 0.4 M
NaOH-0.6 M NaCl, and neutralized in 0.5 M Tris-HCl (pH 7.5)-1.5 M
NaCl for 30 min (13). DNA was transferred
(16) onto nylon membranes (Boehringer Mannheim Corp.,
Indianapolis, Ind.) using a vacuum blotter. Membranes were baked at
80°C for 2 h.
Probe preparation.
The probe was a BamHI (New
England Biolabs) fragment from plasmid pKK 3535 containing E. coli 16S and 23S rRNA genes (12). Digested DNA was
separated in 0.8% agarose gel in TAE buffer for 2 h. at 80 mV.
Insert DNA was purified using the Geneclean system (Bio 101, Carlsbad,
Calif.) as specified by the manufacturer. The probe was labeled with
digoxigenin-dUTP (Boehringer Mannheim Corp.) according to the
manufacturer's instructions.
Hybridization.
Membranes were prehybridized at 65°C for 90 min and hybridized with the probe used as 25 ng of DNA per filter (10 by 15 cm) at 65°C for 16 h in a hybridization oven (Hybaid
Instruments, Holbrook, N.Y.). Membranes were washed twice for 5 min
using 2× SSC (0.3 M NaCl-30 mM sodium citrate)-0.1% sodium dodecyl
sulfate (SDS). Two final 15-min washes were performed with 0.5×
SSC-0.1% SDS at 65°C (13). Membranes were developed
colorimetrically using nitroblue tetrazolium and
5-bromo-4-chloro-3-indolyl-phosphate (BCIP; Boehringer Mannheim Corp.)
according to the manufacturer's instructions.
Statistical analysis.
The method used for the discrimination
of riboprints of E. coli isolated from known-host sources
was based on a previously reported procedure (11).
Riboprints, developed on membranes after hybridization with the
riboprobe, were captured for computer analysis by placement on a
flatbed scanner. Each pattern of bands was converted to a line diagram,
and fragment sizes (in base pairs) were assigned to each band using DNA
Proscan software (Nashville, Tenn.). Riboprint patterns were converted
to a binary code for discriminant analysis (8) performed
in SAS (SAS/STAT [1989] version 6). All or selected portions of the
riboprint patterns were sequentially divided into 8 to 34 equal
segments (windows) extending between 0 and 35 kb. The algorithm
compared pattern profiles by the presence or absence and number of
bands in each window. The number and width of these windows were
adjusted until the accuracy of classification of host patterns reached
its highest attainable level. Discriminant analysis using SAS software
(PROC DISCRIM) was performed as a comparison of riboprints of all eight known-host sources, human versus pooled nonhuman sources, and groups of
three to five selected host classes. Cross-validation iterations were
performed with each riboprint in the database, and the percent correct
classification was determined. Spatial plot display, based on the use
of 24 windows, was projected into two principal variables using SAS
software (PROC CAN DISC). Plots represented a visual interpretation of
pattern analysis. Separation of patterns with respect to the host
source is an indication of accuracy of identification.
| |
RESULTS |
A total of 287 known-host riboprint patterns were generated for
E. coli strains isolated from humans, cattle, pigs, horses, chickens, turkeys, migratory geese, and dogs. These riboprints were
composed of 6 to 12 bands ranging in size from approximately 0.5 to
25.0 kb. Lanes containing the patterns were divided into segments
(windows) of equal size for computer analysis. Best results were
obtained by dividing the 0.5- to 22.0-kb portion of each pattern into
24 equal windows. Rates of correct classification (RCC) for various
combinations of host classes are shown in Tables 2 to
6.
A comparison of human and nonhuman riboprints resulted in 95.0 and
99.19% correct classifications, respectively (Table 2). The average
rate of correct classification (ARCC) for riboprints compared to all
eight host classes simultaneously (Table 3) was 73.56%. When
comparison was made between a more limited number of classes the ARCC
improved. Examples of results obtained from discriminant analyses with
three classes included in each exercise are represented by Tables 4 to
6.
Plots of canonical variables 1 and 2 (Can1 and Can2) on the
x and y axes, respectively, are presented in Fig.
1 to
4.
The variables represent major characteristics used as criteria for the
comparison of riboprints. The resulting spatial display of riboprints
from all eight host classes displayed simultaneously appears in Fig. 1.
In this instance there is a complex and complicated array without
distinct clustering of host-associated patterns. However, comparison of
three host classes at a time resulted in distinct separation of
patterns from each class (Fig. 2 to 4). These visual displays of
cluster association reflect the level of accuracy of classification of
the riboprints of respective host species.
View larger version (10K):
[in this window]
[in a new window]
|
FIG. 1.
Two-dimensional spatial plot of riboprints of fecal
E. coli from all eight host sources studied. Hosts are
identified by the following letters: h, human; p, pig; c, cattle; e,
horse; d, dog; w, chicken; t, turkey; and g, migratory geese. Can1 is
on the x axis, and Can2 is on y axis. There were
84 hidden observation points which were invisible due to overlapping.
|
|
View larger version (7K):
[in this window]
[in a new window]
|
FIG. 2.
Spatial plot of riboprints of fecal E. coli
from cattle, pigs, and humans. Positions of patterns are represented as
follows: c, cattle; p, pigs; and h, humans. Can1 is on the x
axis, and Can2 is on the y axis. There were 28 hidden
observations.
|
|
View larger version (6K):
[in this window]
[in a new window]
|
FIG. 3.
Spatial plot of riboprints of fecal E. coli
from cattle, pigs, and chickens. Positions of patterns are represented
as follows: c, cattle; p, pigs; and w, chickens. Can1 is on the
x axis, and Can2 is on the y axis. There were 21 hidden observations.
|
|
View larger version (8K):
[in this window]
[in a new window]
|
FIG. 4.
Spatial plot of riboprints of fecal E. coli
from humans, dogs, and geese. Positions of patterns are represented as
follows: h, humans; d, dogs; and g, geese. Can1 is on the x
axis, and Can2 is on the y axis. There were 24 hidden
observations.
|
|
| |
DISCUSSION |
We have tested the use of riboprinting for identification of fecal
E. coli from specific sources. This method proved to be quite accurate for discriminating between riboprint patterns of human
and nonhuman origin, with an ARCC of 97.10%. The RCC of riboprints,
from each of the eight known-host sources studied, ranged between 48.65 and 95.65% when compared simultaneously (Table 3). However, it was
shown that the accuracy of classification can be greatly increased by
limiting the number of classes compared (Tables 2 to 6). Similarly, the
spatial analysis of all patterns simultaneously did not distinctly
cluster the host sources. When each clustering iteration was limited to
three host sources, such as cattle, pigs, and humans (Fig. 2),
chickens, pigs, and cattle (Fig. 3), or geese, humans, and dogs (Fig.
4), it became possible to distinguish riboprints representing E. coli from particular hosts.
Application of this technology to testing water quality is our ultimate
goal. This approach would require riboprinting of unknown-source
E. coli in water samples and comparison of the resultant
patterns with known-host patterns in the database. For example, Fig. 3
provides a distinct display of fecal coliform riboprints from three of
the most common animal species involved in concentrated feeding
operations
cattle, chickens, and pigsindicating that unknowns
compared to particular known-host patterns may be accurately
characterized. In analyses of municipal storm water the suspected
pollution sources may include humans, dogs, or migratory geese. The
associated patterns in Fig. 4 form fairly distinct clusters, indicating
good probability for correct classification. In field situations it is
also recommended that additional samples of host sources in the local
landscape be included in the database for discriminant analysis of
unknown E. coli isolated from waters under study. This
measure could prove to be important if the geographic location affects
host intestinal flora.
Undoubtedly, there are instances where fecal E. coli
pollutants in water may come from a large number of contributing host sources, consequently increasing the rates of misclassification by
ribotyping. Commonly, there will also be instances of application of
ribotyping for microbial source tracking where there will be only a few
obvious potential sources of pollution. In these latter situations we
would propose that the fingerprinting scheme presented here will be
more accurate in the rate of correct classification of riboprints.
As with other DNA fingerprinting methods, ribotyping produces various
patterns that represent the genomic similarity or dissimilarity between
isolates. Certain fecal E. coli riboprints appear to be associated with (if not unique) to certain host classes. We can only
speculate as to why this phenomenon may occur and suppose that factors
affecting the microenvironment of particular host intestines, including
temperature, pH, and diet may be associated with strain selection or
enrichment. Seasonal, geographic, or genetic variation in natural
fecal E. coli populations may also occur, but
these issues were not examined in the present study. Based on a study
of host-associated E. coli strains by multiple antibiotic
resistance profiles, there is reportedly little or no
cross-colonization (9). It has also been reported that
different host classes harbor E. coli which have very
similar or identical riboprints (11), and consequently
misclassification may occur in these instances.
It appears that typical enteric populations of E. coli
within each host species studied are significantly different for
ribotyping to serve as a valuable means for identification of sources
of fecal pollution. Reported results are based on a modest database of
287 patterns. The accuracy of results is expected to increase as the
database of known-host samples is expanded. For practical application
of this technology to water quality, it will also be valuable to
include additional host sources of E. coli in our database.
| |
ACKNOWLEDGMENTS |
This work was supported by the University of Missouri Outreach
and Extension, Columbia, Mo., and the U.S. Geological Survey, Rolla, Mo.
We thank Salina Parveen (University of Florida) for advice and methods
information and Shaun Tyler (Health Canada) for plasmid pKK3535 used in
preparing the riboprobe. We are also grateful to John Schumacher and
Don Wilkison (U.S. Geological Survey), Mike Monda (U.S. Army Corps of
Engineers), and John Knudsen and Michael Heaton (Missouri Department of
Natural Resources) for assistance in sample collection.
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Veterinary Pathobiology, 201 Connaway Hall, University of Missouri,
Columbia, MO 65211. Phone: (573) 884-7640. Fax: (573) 884-0521. E-mail: carsonc{at}missouri.edu.
| |
REFERENCES |
| 1.
|
American Public Health Association.
1995.
Standard methods for the examination of water and wastewater, 19th ed.
American Public Health Association, Washington, D.C.
|
| 2.
|
Bernhard, A. E., and K. G. Field.
2000.
A PCR assay to discriminate human and animal feces on the basis of host differences in Bacteroides-Prevotella genes encoding 16S rRNA.
Appl. Environ. Microbiol.
66:4571-4574[Abstract/Free Full Text].
|
| 3.
|
Dombek, P. E.,
L. K. Johnson,
S. J. Zimmerley, and M. J. Sadowsky.
2000.
Use of repetitive DNA sequences and the PCR to differentiate Escherichia coli isolates from human and animal sources.
Appl. Environ. Microbiol.
66:2572-2577[Abstract/Free Full Text].
|
| 4.
|
Fleisher, J. M.,
D. Kay,
R. L. Salmen,
F. Jones,
M. D. Wyer, and A. F. Godfree.
1996.
Marine waters, contaminated with domestic sewage: nonenteric illnesses associated with bather exposure in the United Kingdom.
Am. J. Public Health
86:1228-1234[Abstract/Free Full Text].
|
| 5.
|
Geldreich, E. E., and B. A. Kenner.
1969.
Concepts of fecal streptococci in stream pollution.
J. Water Pollut. Control Fed.
41:R336-R352.
|
| 6.
|
Hagedorn, C.,
S. L. Robinson,
J. R. Filtz,
S. M. Grubbs,
T. A. Angier, and R. B. Reneau, Jr.
1999.
Determining sources of fecal pollution in rural Virginia watershed with antibiotic resistance patterns in fecal streptococci.
Appl. Environ. Microbiol.
65:5522-5531[Abstract/Free Full Text].
|
| 7.
|
Harwood, V. J.,
J. Whitlock, and V. Withington.
2000.
Classification of antibiotic resistance patterns of indicator bacteria by discriminant analysis: use in predicting the source of fecal contamination in subtropical waters.
Appl. Environ. Microbiol.
66:3698-3704[Abstract/Free Full Text].
|
| 8.
|
Johnson, R. A., and D. W. Wichern.
1992.
Applied multivariate statistical analysis, 3rd ed.
Prentice-Hall, Inc., Englewood Cliffs, N.J.
|
| 9.
|
Kariuki, S.,
C. Gilks,
J. Kimari,
A. Obanda,
J. Muyodi,
P. Waiyaki, and C. A. Hart.
1999.
Genotype analysis of Escherichia coli strains isolated from children and chickens living in close contact.
Appl. Environ. Microbiol.
65:472-476[Abstract/Free Full Text].
|
| 10.
|
Parveen, S.,
R. L. Murphree,
L. Edmiston,
C. W. Kaspar,
K. M. Portier, and M. L. Tamplin.
1997.
Association of multiple-antibiotic resistance profiles with point and nonpoint sources of Escherchia coli in Apalachicola Bay.
Appl. Environ. Microbiol.
63:2607-2612[Abstract].
|
| 11.
|
Parveen, S.,
K. M. Portier,
K. Robinson,
L. Edmiston, and M. L. Tamplin.
1999.
Discriminant analysis of ribotype profiles of Escherichia coli for differentiating human and nonhuman sources of fecal pollution.
Appl. Environ. Microbiol.
65:3142-3147[Abstract/Free Full Text].
|
| 12.
|
Regnault, B.,
F. Grimont, and P. A. D. Grimont.
1997.
Universal ribotyping method using a chemically labelled oligonucleotide probe mixture.
Res. Microbiol.
148:649-659[Medline].
|
| 13.
|
Sambrook, J.,
E. F. Fritsch, and T. Maniatis.
1989.
Molecular cloning: a laboratory manual, 2nd ed.
Cold Spring Harbor Laboratory, Cold Spring Harbor, N.Y.
|
| 14.
|
SAS Institute, Inc.
1989.
SAS/STAT user's guide, version 6, 4th ed., vol. 1.
SAS Institute, Inc., Cary, N.C.
|
| 15.
|
Sauer, T. J.,
T. C. Daniel,
D. J. Nichols,
C. P. West,
P. A. Moore, Jr., and G. L. Wheeler.
2000.
Runoff water quality from poultry litter-treated pasture and forest sites.
J. Environ. Qual.
29:515-521[Abstract/Free Full Text].
|
| 16.
|
Southern, E. M.
1975.
Detection of specific sequences among DNA fragments separated by gel electrophoresis.
J. Mol. Biol.
98:503-517[CrossRef][Medline].
|
| 17.
|
U.S. Environmental Protection Agency.
1998.
1998
In
TMDL tracking system data, version 1.0. Total maximum daily load program. U.S. Environmental Protection Agency Office of Water, Washington, D.C. [Online.] http: //www.epa.gov/owow/tmdl/trcksys.html
|
| 18.
|
Wiggins, B. A.
1996.
Discriminant analysis of antibiotic resistance patterns in fecal streptococci, a method to differentiate human and animal sources of fecal pollution in natural waters.
Appl. Environ. Microbiol.
62:3997-4002[Abstract].
|
| 19.
|
Wiggins, B. A.,
R. W. Andrews,
R. A. Conway,
C. L. Corr,
E. J. Dobratz,
D. P. Dougherty,
F. R. Eppard,
S. R. Knupp,
M. C. Limjoco,
J. M. Mettenburg,
J. M. Rinehardt,
J. Sonsino,
R. L. Torrijos, and M. E. Zimmerman.
1999.
Use of antibiotic resistance analysis to identify nonpoint sources of fecal pollution.
Appl. Environ. Microbiol.
65:3483-3486[Abstract/Free Full Text].
|
| 20.
|
Zierdt, C. H.,
E. A. Robertson,
R. L. Williams, and J. D. MacLowry.
1980.
Computer analysis of Staphylococcus aureus phage typing data from 1957 to 1975, citing epidemiological trends and natural evolution within phage typing system.
Appl. Environ. Microbiol.
39:623-629[Abstract/Free Full Text].
|
Applied and Environmental Microbiology, April 2001, p. 1503-1507, Vol. 67, No. 4
0099-2240/01/$04.00+0 DOI: 10.1128/AEM.67.4.1503-1507.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
This article has been cited by other articles:
-
Bolster, C. H., Haznedaroglu, B. Z., Walker, S. L.
(2009). Diversity in Cell Properties and Transport Behavior among 12 Different Environmental Escherichia coli Isolates. J. Environ. Qual.
38: 465-472
[Abstract]
[Full Text]
-
Sharma, R., Munns, K., Alexander, T., Entz, T., Mirzaagha, P., Yanke, L. J., Mulvey, M., Topp, E., McAllister, T.
(2008). Diversity and Distribution of Commensal Fecal Escherichia coli Bacteria in Beef Cattle Administered Selected Subtherapeutic Antimicrobials in a Feedlot Setting. Appl. Environ. Microbiol.
74: 6178-6186
[Abstract]
[Full Text]
-
Dickerson, J. W. Jr., Crozier, J. B., Hagedorn, C., Hassall, A.
(2007). Assessment of the 16S-23S rDNA Intergenic Spacer Region in Enterococcus spp. for Microbial Source Tracking. J. Environ. Qual.
36: 1661-1669
[Abstract]
[Full Text]
-
Baertsch, C., Paez-Rubio, T., Viau, E., Peccia, J.
(2007). Source Tracking Aerosols Released from Land-Applied Class B Biosolids during High-Wind Events. Appl. Environ. Microbiol.
73: 4522-4531
[Abstract]
[Full Text]
-
Ruecker, N. J., Braithwaite, S. L., Topp, E., Edge, T., Lapen, D. R., Wilkes, G., Robertson, W., Medeiros, D., Sensen, C. W., Neumann, N. F.
(2007). Tracking Host Sources of Cryptosporidium spp. in Raw Water for Improved Health Risk Assessment. Appl. Environ. Microbiol.
73: 3945-3957
[Abstract]
[Full Text]
-
Kaneene, J. B., Miller, R., Sayah, R., Johnson, Y. J., Gilliland, D., Gardiner, J. C.
(2007). Considerations When Using Discriminant Function Analysis of Antimicrobial Resistance Profiles To Identify Sources of Fecal Contamination of Surface Water in Michigan. Appl. Environ. Microbiol.
73: 2878-2890
[Abstract]
[Full Text]
-
Stoeckel, D. M., Harwood, V. J.
(2007). Performance, Design, and Analysis in Microbial Source Tracking Studies. Appl. Environ. Microbiol.
73: 2405-2415
[Full Text]
-
Kirs, M., Smith, D. C.
(2007). Multiplex Quantitative Real-Time Reverse Transcriptase PCR for F+-Specific RNA Coliphages: a Method for Use in Microbial Source Tracking. Appl. Environ. Microbiol.
73: 808-814
[Abstract]
[Full Text]
-
Anderson, M. A., Whitlock, J. E., Harwood, V. J.
(2006). Diversity and Distribution of Escherichia coli Genotypes and Antibiotic Resistance Phenotypes in Feces of Humans, Cattle, and Horses. Appl. Environ. Microbiol.
72: 6914-6922
[Abstract]
[Full Text]
-
Soule, M., Kuhn, E., Loge, F., Gay, J., Call, D. R.
(2006). Using DNA microarrays to identify library-independent markers for bacterial source tracking.. Appl. Environ. Microbiol.
72: 1843-1851
[Abstract]
[Full Text]
-
Ishii, S., Ksoll, W. B., Hicks, R. E., Sadowsky, M. J.
(2006). Presence and Growth of Naturalized Escherichia coli in Temperate Soils from Lake Superior Watersheds. Appl. Environ. Microbiol.
72: 612-621
[Abstract]
[Full Text]
-
Fogarty, L. R., Voytek, M. A.
(2005). Comparison of Bacteroides-Prevotella 16S rRNA Genetic Markers for Fecal Samples from Different Animal Species. Appl. Environ. Microbiol.
71: 5999-6007
[Abstract]
[Full Text]
-
Ahmed, W., Neller, R., Katouli, M.
(2005). Host Species-Specific Metabolic Fingerprint Database for Enterococci and Escherichia coli and Its Application To Identify Sources of Fecal Contamination in Surface Waters. Appl. Environ. Microbiol.
71: 4461-4468
[Abstract]
[Full Text]
-
Lasalde, C., Rodriguez, R., Toranzos, G. A.
(2005). Statistical Analyses: Possible Reasons for Unreliability of Source Tracking Efforts. Appl. Environ. Microbiol.
71: 4690-4695
[Abstract]
[Full Text]
-
Carson, C. A., Christiansen, J. M., Yampara-Iquise, H., Benson, V. W., Baffaut, C., Davis, J. V., Broz, R. R., Kurtz, W. B., Rogers, W. M., Fales, W. H.
(2005). Specificity of a Bacteroides thetaiotaomicron Marker for Human Feces. Appl. Environ. Microbiol.
71: 4945-4949
[Abstract]
[Full Text]
-
Anderson, K. L., Whitlock, J. E., Harwood, V. J.
(2005). Persistence and Differential Survival of Fecal Indicator Bacteria in Subtropical Waters and Sediments. Appl. Environ. Microbiol.
71: 3041-3048
[Abstract]
[Full Text]
-
Sayah, R. S., Kaneene, J. B., Johnson, Y., Miller, R.
(2005). Patterns of Antimicrobial Resistance Observed in Escherichia coli Isolates Obtained from Domestic- and Wild-Animal Fecal Samples, Human Septage, and Surface Water. Appl. Environ. Microbiol.
71: 1394-1404
[Abstract]
[Full Text]
-
Hassan, W. M., Wang, S. Y., Ellender, R. D.
(2005). Methods To Increase Fidelity of Repetitive Extragenic Palindromic PCR Fingerprint-Based Bacterial Source Tracking Efforts. Appl. Environ. Microbiol.
71: 512-518
[Abstract]
[Full Text]
-
Johnson, L. K., Brown, M. B., Carruthers, E. A., Ferguson, J. A., Dombek, P. E., Sadowsky, M. J.
(2004). Sample Size, Library Composition, and Genotypic Diversity among Natural Populations of Escherichia coli from Different Animals Influence Accuracy of Determining Sources of Fecal Pollution. Appl. Environ. Microbiol.
70: 4478-4485
[Abstract]
[Full Text]
-
McLellan, S. L.
(2004). Genetic Diversity of Escherichia coli Isolated from Urban Rivers and Beach Water. Appl. Environ. Microbiol.
70: 4658-4665
[Abstract]
[Full Text]
-
Bonjoch, X., Balleste, E., Blanch, A. R.
(2004). Multiplex PCR with 16S rRNA Gene-Targeted Primers of Bifidobacterium spp. To Identify Sources of Fecal Pollution. Appl. Environ. Microbiol.
70: 3171-3175
[Abstract]
[Full Text]
-
Ram, J. L., Ritchie, R. P., Fang, J., Gonzales, F. S., Selegean, J. P.
(2004). Sequence-Based Source Tracking of Escherichia coli Based on Genetic Diversity of {beta}-Glucuronidase. J. Environ. Qual.
33: 1024-1032
[Abstract]
[Full Text]
-
Yang, H.-H., Vinopal, R. T., Grasso, D., Smets, B. F.
(2004). High Diversity among Environmental Escherichia coli Isolates from a Bovine Feedlot. Appl. Environ. Microbiol.
70: 1528-1536
[Abstract]
[Full Text]
-
Seurinck, S., Verstraete, W., Siciliano, S. D.
(2003). Use of 16S-23S rRNA Intergenic Spacer Region PCR and Repetitive Extragenic Palindromic PCR Analyses of Escherichia coli Isolates To Identify Nonpoint Fecal Sources. Appl. Environ. Microbiol.
69: 4942-4950
[Abstract]
[Full Text]
-
Wiggins, B. A., Cash, P. W., Creamer, W. S., Dart, S. E., Garcia, P. P., Gerecke, T. M., Han, J., Henry, B. L., Hoover, K. B., Johnson, E. L., Jones, K. C., McCarthy, J. G., McDonough, J. A., Mercer, S. A., Noto, M. J., Park, H., Phillips, M. S., Purner, S. M., Smith, B. M., Stevens, E. N., Varner, A. K.
(2003). Use of Antibiotic Resistance Analysis for Representativeness Testing of Multiwatershed Libraries. Appl. Environ. Microbiol.
69: 3399-3405
[Abstract]
[Full Text]
-
McLellan, S. L., Daniels, A. D., Salmore, A. K.
(2003). Genetic Characterization of Escherichia coli Populations from Host Sources of Fecal Pollution by Using DNA Fingerprinting. Appl. Environ. Microbiol.
69: 2587-2594
[Abstract]
[Full Text]
-
Carson, C. A., Shear, B. L., Ellersieck, M. R., Schnell, J. D.
(2003). Comparison of Ribotyping and Repetitive Extragenic Palindromic-PCR for Identification of Fecal Escherichia coli from Humans and Animals. Appl. Environ. Microbiol.
69: 1836-1839
[Abstract]
[Full Text]
-
Scott, T. M., Parveen, S., Portier, K. M., Rose, J. B., Tamplin, M. L., Farrah, S. R., Koo, A., Lukasik, J.
(2003). Geographical Variation in Ribotype Profiles of Escherichia coli Isolates from Humans, Swine, Poultry, Beef, and Dairy Cattle in Florida. Appl. Environ. Microbiol.
69: 1089-1092
[Abstract]
[Full Text]
-
Jenkins, M. B., Hartel, P. G., Olexa, T. J., Stuedemann, J. A.
(2003). Putative Temporal Variability of Escherichia coli Ribotypes from Yearling Steers. J. Environ. Qual.
32: 305-309
[Abstract]
[Full Text]
-
Scott, T. M., Rose, J. B., Jenkins, T. M., Farrah, S. R., Lukasik, J.
(2002). Microbial Source Tracking: Current Methodology and Future Directions. Appl. Environ. Microbiol.
68: 5796-5803
[Full Text]
-
Schaper, M., Duran, A. E., Jofre, J.
(2002). Comparative Resistance of Phage Isolates of Four Genotypes of F-Specific RNA Bacteriophages to Various Inactivation Processes. Appl. Environ. Microbiol.
68: 3702-3707
[Abstract]
[Full Text]
-
Hartel, P. G., Summer, J. D., Hill, J. L., Collins, J. V., Entry, J. A., Segars, W. I.
(2002). Geographic Variability of Escherichia coli Ribotypes from Animals in Idaho and Georgia. J. Environ. Qual.
31: 1273-1278
[Abstract]
[Full Text]
-
Wheeler, A. L., Hartel, P. G., Godfrey, D. G., Hill, J. L., Segars, W. I.
(2002). Potential of Enterococcus faecalis as a Human Fecal Indicator for Microbial Source Tracking. J. Environ. Qual.
31: 1286-1293
[Abstract]
[Full Text]
-
Graves, A. K., Hagedorn, C., Teetor, A., Mahal, M., Booth, A. M., Reneau, R. B. Jr.
(2002). Antibiotic Resistance Profiles to Determine Sources of Fecal Contamination in a Rural Virginia Watershed. J. Environ. Qual.
31: 1300-1308
[Abstract]
[Full Text]
Top
Abstract
Introduction
