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U.S. Department of the InteriorU.S. Geological Survey
Open-File Report 2015–1013
Prepared in cooperation with the Great Lakes Restoration Initiative
Occurrence and Distribution of Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries, March–October 2011
Cover: Bad River, Wisconsin (photo by Eric Dantoin, U.S. Geological Survey).
Occurrence and Distribution of Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries, March–October 2011
By Angela K. Brennan, Heather E. Johnson, Alex R. Totten, and Joseph W. Duris
Prepared in cooperation with the Great Lakes Restoration Initiative
Open-File Report 2015–1013
U.S. Department of the InteriorU.S. Geological Survey
U.S. Department of the InteriorSALLY JEWELL, Secretary
U.S. Geological SurveySuzette M. Kimball, Acting Director
U.S. Geological Survey, Reston, Virginia: 2015
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Suggested citation:Brennan, A.K., Johnson, H.E., Totten, A.R., and Duris, J.W., 2015, Occurrence and distribution of fecal indicator bacte-ria and gene markers of pathogenic bacteria in Great Lakes tributaries, March–October 2011: U.S. Geological Survey Open-File Report 2015–1013, 29 p., http://dx.doi.org/10.3133/ofr20151013.
ISSN 2331-1258 (online)
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Contents
Abstract ...........................................................................................................................................................1Introduction.....................................................................................................................................................1
Purpose and Scope ..............................................................................................................................2Description of Study Area ...................................................................................................................2
Sampling and Analytical Methods ..............................................................................................................2Site Selection.........................................................................................................................................2Sample Collection .................................................................................................................................2Microbiological Analyses ...................................................................................................................6
Bacteria Enumeration, Enrichment, and Preservation ..........................................................6DNA Extraction .............................................................................................................................6Polymerase Chain Reaction Assays for Pathogen Detection ..............................................6
Results of Microbiological Analyses ..........................................................................................................6Occurrence and Distribution of Fecal Indicator Bacteria .............................................................6Occurrence and Distribution of Bacterial Pathogen Gene Markers ...........................................8
Quality-Control Results ...............................................................................................................................10Summary........................................................................................................................................................10Acknowledgements .....................................................................................................................................11References Cited..........................................................................................................................................11Appendixes ................................................................................................................................................13
Figures 1. Graph showing land cover surrounding tributary sites sampled as part of the
Great Lakes Restoration Initiative (GLRI) pathogens study ...................................................3 2. Map showing Great Lakes Restoration Initiative (GLRI) USGS tributary sampling
locations and number of samples collected for pathogens study, 2011 .............................4 3. Graph showing frequency of samples testing positive for pathogen gene markers ........8 4. Graph showing percentage of pathogen gene markers in relation to water quality
criteria.....................................................................................................................................................9
Tables 1. Great Lakes Restoration Initiative (GLRI) pathogens study sampling locations, 2011 ......5 2. Growth media, target organisms, and incubation temperature requirements for the
Great Lakes Restoration Initiative (GLRI) pathogens study ...................................................7 3. Selected pathogen gene targets and virulence traits of the organism ...............................7 4. Summary of the frequency of pathogen gene detections in a single sample. ...................8 5. Percentage of samples that tested positive for pathogenic gene markers during
high-flow and normal-flow conditions ......................................................................................9 6. Relative standard deviation of field replicates for quantitative microbial methods
in the Great Lakes Restoration Initiative (GLRI) pathogens study ......................................10 7. Frequency of agreement between field replicates for qualitative microbial
methods in the Great Lakes Restoration Initiative (GLRI) pathogens study .....................10
iv
Multiply By To obtain
Length
mile (mi) 1.609 kilometer (km)Area
square mile (mi2) 2.590 square kilometer (km2) Volume
milliliter (mL) 1,000 microliter (µL)
Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows: °F=(1.8×°C)+32Horizontal coordinate information is referenced to North American Datum of 1983 (NAD 83).Concentrations of fecal indicator bacteria are given in colony-forming units per 100 milliliters (CFU/100 mL).
Conversion Factors
v
Abbreviations used in report
CDC Centers for Disease Control and Prevention
CFU colony-forming unit
DNA Deoxyribonucleic acid
E. coli Escherichia coli
EWI equal-width-increment
FIB Fecal indicator bacteria
GLRI Great Lakes Restoration Initiative
MI-BaRL USGS Michigan Bacteriological Research Laboratory
MI-WSC USGS Michigan Water Science Center
PBS phosphate buffered saline
PCR polymerase chain reaction
QC quality control
RSD relative standard deviation
STEC Shiga-toxin producing Escherichia coli
EPA U.S. Environmental Protection Agency
USGS U.S. Geological Survey
WQC water quality criteria
Occurrence and Distribution of Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries, March–October 2011
By Angela K. Brennan, Heather E. Johnson, Alex R. Totten, and Joseph W. Duris
AbstractFrom March through October 2011, the U.S. Geological
Survey (USGS), conducted a study to determine the frequency of occurrence of pathogen gene markers and densities of fecal indicator bacteria (FIB) in 22 tributaries to the Great Lakes. This project was funded as part of the Great Lakes Restora-tion Initiative (GLRI) and included sampling at 22 locations throughout 6 states that border the Great Lakes.
A total of 177 environmental samples were collected at USGS streamgaging stations during both normal-flow and high-flow conditions and were analyzed by the Michigan Bac-teriological Research Laboratory at the USGS Water Science Center in Lansing, Michigan.
Water samples were analyzed for the presence of FIB concentrations (FIB; fecal coliform bacteria, Escherichia coli [E. coli], and enterococci) by using membrane filtration and serial dilution methods. The resulting enrichments from standard culturing of the samples were then analyzed by using polymerase chain reaction (PCR) to determine the occurrence of pathogen gene markers for Shigella species, Campylobacter jejuni and coli, Salmonella species, and pathogenic E. coli, including Shiga toxin-producing E. coli (STEC).
IntroductionIn 2009, the Great Lakes Restoration Initiative (GLRI)
was started as an interagency initiative to protect and restore the Great Lakes. This report describes data collected in 2011 as part of the U.S. Geological Survey (USGS) GLRI effort led by the Michigan Water Science Center (MI-WSC), in conjunc-tion with USGS Water Science Centers in Indiana, Minnesota, Ohio, New York, and Wisconsin, and complements the ongo-ing USGS GLRI Great Lakes Nutrient and Sediment Loadings study (GLRI Loadings study) being conducted at the same sampling locations.
The microbiological monitoring network for this study consisted of 22 sampling locations, representing multiple land-use types, drainage areas, and soil characteristics typical of the Great Lakes region. Samples were collected to better understand the occurrence and distribution of fecal indicator bacteria (FIB) and selected bacterial pathogens that are com-monly associated with waterborne illnesses.
Within the broad FIB groups (Escherichia coli [E. coli], fecal coliforms, and enterococci), there are specific strains of bacteria that are pathogenic (infection causing) to humans. The bacterial pathogen gene markers evaluated in this study included genes from the genera Shigella, Campylobacter (jejuni and coli) and Salmonella. In addition, several genes were also evaluated from a class of pathogenic E. coli known as Shiga toxin-producing E. coli (STEC), which includes E. coli O157:H7.
Fecally derived bacterial pathogens have long been known to be a health threat to humans, and exposure to these pathogens can result in illness and occasionally even death (Centers for Disease Control and Prevention [CDC], 2012b). STEC, including E. coli O157:H7, can cause illness ranging from mild intestinal disease to severe kidney complications and death in animals and humans (CDC, 2012d). Shigella’s pathogenicity functions similarly to that of STEC; however, Shigella mainly affects humans. Campylobacter is one of the most common causes of diarrheal illness in the United States, and symptoms include cramping, abdominal pain, and fever (CDC, 2012a). Salmonella infection can cause diarrhea, fever, and abdominal cramps, and severe cases can even lead to death (CDC, 2012c).
Current methods for evaluating recreational and drinking water safety typically rely on the enumeration of FIB (U.S. Environmental Protection Agency [EPA], 2012). FIB are used to indicate the potential for illness associated with fecal contamination (EPA, 2012). Primary contact refers to water-contact activities where immersion and ingestion are likely, such as swimming, water skiing, and diving. Even though most tributaries are not used for “primary contact” recreational
2 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries
water activities, many of these major tributaries enter the Great Lakes at or near a beach which is designated as a recre-ation area. Most tributaries are used for partial, or secondary, contact recreation, indicating water activities where there is the potential of submergence, such as boating and fishing. FIB concentrations and the occurrence of bacterial pathogens associated with these bodies of water are important, not only to partial contact recreational users in rivers but ultimately to primary contact recreational users at Great Lakes beaches. The partial body contact recreation standard (Dufour and Bal-lantine, 1986) was used for data interpretation for this report because the EPA 2012 guidance does not include a numerical standard for partial body contact in recreational waters.
Purpose and Scope
This report presents data obtained during a Great Lakes-wide study conducted in 2011 by the USGS as part of the GLRI. The purpose of this study was to determine the occur-rence and distribution of FIB and pathogenic gene markers within 22 major tributaries to the Great Lakes. Normal-flow and high-flow samples were analyzed for FIB and for patho-gens Shigella, Campylobacter (jejuni and coli), Salmonella, and STEC, which included E. coli O157:H7. The relations of FIB concentrations and bacterial pathogen gene occurrence to recreational water quality criteria were also assessed.
Description of Study Area
Approximately 132,208 miles of tributaries (EPA and USGS, 2012), with a drainage area of almost 295,000 square miles (Great Lakes Information Network, 2013), drain into the Great Lakes from six states (Indiana, Michigan, Minnesota, New York, Ohio, Wisconsin) and Canada. The 22 monitoring locations are grouped on the basis of predominant land cover surrounding the major tributaries in this study (fig. 1) (USGS, 2011) and were distributed geographically throughout the Great Lakes region of the United States (fig. 2).
Sampling and Analytical Methods
Site Selection
All sampling locations were at USGS streamgaging stations. Twenty-two sampling locations (fig. 2, table 1) were selected (out of 59 GLRI Loadings study sites) to create a geo-graphically distributed study and to address the variability in land cover throughout the Great Lakes region. Sampling loca-tions, as well as timing of sample collection, were designed to complement the GLRI Loadings study (USGS, 2014). In addi-tion to those sites selected from the GLRI Loadings study, the Paw Paw River at Riverside, MI, was included as a sampling location for this study because the site was routinely visited as part of another USGS MI-WSC project.
Sample Collection
Hydrologic conditions were determined on the basis of mean daily discharge1 at each USGS streamgage on the date of collection, calculated from date of first record to current. Con-ditions were evaluated such that if daily discharge2 was greater than or equal to the 75th percentile, the corresponding sample was considered a high-flow sample; otherwise, the sample was considered a normal-flow sample. Owing to a short period of record, the Grand River at Grand Rapids station was used to estimate hydrologic conditions for the Grand River at Eastmanville station. Water samples were collected during normal-flow conditions from March through October 2011 in an effort to target the recreational water season. Samples were also collected during high-flow conditions (storm events), but sampling frequency varied among sites in response to the frequency of storm events and availability of staff (table 1).
The sampling frequency depended on the sampling schedule of the GLRI Loadings study. Some sites were sampled more often than others, including those sites targeted for analysis of certain chemical constituents (such as waste-water indicator compounds) in addition to FIB and pathogenic gene markers.
Normal-flow and high-flow sampling events typically coincided with GLRI Loadings study sampling. All samples were collected by USGS personnel using either equal-width-increment (EWI) or multiple vertical sampling techniques designed to account for the variable distribution of constitu-ents across the stream channel and throughout the water column (USGS, 2006). EWI samples were typically collected off bridges by using a crane apparatus with an attached DH-95 depth integrating sampler, or from boats. There were instances when wading measurements were made, but typically only during normal-flow conditions.
For each sample, a 1-liter sterile high density polyethyl-ene (HDPE) sample bottle was filled to the shoulder to allow some head space for sample mixing. Once collected, water samples were placed on ice in a cooler (away from ultraviolet light) and shipped overnight to the MI-BaRL (Michigan Bac-teriological Research Laboratory) at the MI-WSC in Lansing, Michigan. Upon receipt of the shipments, sample information and streamflow condition were logged in to the laboratory database system, and samples were placed into the refrigerator at 4–7 degrees Celsius (°C) until processing and analysis (typi-cally the same day).
A total of 177 water samples were collected, including field quality-control (QC) samples. There were 59 normal-flow samples and 54 high-flow samples used for data analysis. Quality-control samples included 21 field blank samples, 21 source solution blank samples, and 22 field replicate samples.
1The arithmetic mean of discharges for all instances of a particular calendar day on record or for a specific set of years.
2The arithmetic mean discharge for a single day.
Sampling and Analytical Methods 3
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4 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries
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Sampling and Analytical Methods 5
Field blanks, source solution blanks, and field replicate sam-ples were collected according to the methods described in the USGS National Field Manual, with inorganic-grade reagent water being used as the sample medium (USGS, 2006). Twelve samples were excluded from the data analysis because the samples exceeded the holding time (48 hours) established
by the MI-BaRL for FIB culturing for nonregulatory purposes. There were also three instances where the bacteria plates were uncountable (coded as “unc”), owing to smearing or a heavy amount of particulates on the filter. A total of 165 water samples were included in the final analysis.
Table 1. Great Lakes Restoration Initiative (GLRI) pathogens study sampling locations, 2011.
[nr, near]
USGS site nameUSGS site
identification number
Field ID
Number of samples collected during
normal flow
Number of samples collected during
high flow
Indiana
Burns Ditch at Portage 04095090 BN 3 4MichiganAu Sable River nr Au Sable 04137500 AU 5 1Clinton River at Moravian Drive at Mt. Clemens 04165500 CL 0 2Grand River nr Eastmanville 04119400 GR 0 5Ontonagon River nr Rockland 04040000 ON 8 1Paw Paw River at Riverside 04102500 PP 2 5River Rouge at Detroit 04166500 RR 1 2River Raisin nr Monroe 04176500 RS 2 0Saginaw River at Saginaw 04157000 SG 5 3St. Joseph River at Niles 04101500 SJ 3 4
Minnesota
St. Louis River at Scanlon 04024000 ST 7 2New York
Genessee River at Ford St. Bridge at Rochester 04231600 GS 3 3Oswego River at Lock 7 at Oswego 04249000 OS 4 4St. Regis River at Brasher Center 04269000 SR 5 5
Ohio
Cuyahoga River at Independence 04208000 CY 1 4Maumee River at Waterville 04193500 MA 2 1Portage River at Woodville 04195500 PO 0 3
Wisconsin
Bad River nr Odanah 04027000 BD 3 1Fox River at Oil Tank Depot at Green Bay 040851385 FX 1 1Menominee River nr McAllister 04067500 MM 2 0Manitowoc River at Manitowoc 04085427 MN 1 1Milwaukee River at Milwaukee 04087170 MW 1 1
6 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries
Microbiological Analyses
Bacteria Enumeration, Enrichment, and Preservation
Water samples were analyzed for the presence of FIB and FIB concentrations by using standard membrane filtration and serial dilution methods (Myers and others, 2014). Fecal coli-form bacteria were analyzed according to standard methods of the American Public Health Association and others (1998), E. coli bacteria were analyzed according to EPA method 1603 (EPA, 2009a), and enterococci bacteria were analyzed accord-ing to EPA method 1600 (EPA, 2009b). Media were prepared according to manufacturer’s instructions.
A volume of 50 milliliters (mL) of sample water was filtered through a 0.45-micrometer-pore-size nylon-membrane filter (Advantec, USA) by means of aseptic techniques. The enriched filter was then placed on a selective growth medium for enumeration and enrichment of target bacterial pathogen groups and incubated at the optimal temperature (table 2).
The filters with E. coli, enterococci, and fecal coliform bacteria growth were transferred to a vial containing 1 mL of phosphate buffered saline solution (PBS), preserved with 20 percent glycerol, and frozen at −70 °C until further analysis; these samples are referred to as “glycerol stocks.” The filters with Campylobacter and Salmonella growth were aseptically removed from the Gram Negative and Bolton Broth enrich-ments, and the remaining culture was centrifuged to form a pellet. The supernatant was decanted, and the pellet was resuspended in 1 mL of PBS solution and preserved with 20 percent glycerol and frozen at −70 °C until deoxyribonucleic acid (DNA) extraction.
DNA ExtractionGlycerol stocks were thawed at room temperature and
DNA was extracted by using the Qiagen QIAamp® DNA Mini Kit (Qiagen, USA), following the manufacturers proto-col. DNA concentrations and purity were determined with a NanoDrop spectrophotometer (Thermo Scientific, USA). DNA was then stored at −20 °C until needed for Polymerase Chain Reaction (PCR) analysis for the selected gene targets (table 3).
Polymerase Chain Reaction Assays for Pathogen Detection
Samples were analyzed by using PCR to determine the occurrence of pathogen gene markers for Shigella sonnei, Campylobacter jejuni and coli, Salmonella, and STEC. The primer sequences, positive controls, reaction details, and qual-ity-control procedures used for the detection of the pathogens by PCR listed in table 3 were based on previously published studies (Haack and others, 2013).
All PCR assays were performed by using 1 microliter of DNA solution, representing 0.1–85 nanograms of template DNA, which was isolated from the appropriate growth enrich-ment. Results from these analyses indicated whether the target genes were present or absent in the sample above the method detection limit; however, PCR does not quantify the genes present. In order for the gene to be detected, the organism had to grow on the appropriate medium, and therefore must have been viable in the sample.
Laboratory filtration blanks were processed daily with every set of samples on all growth media and enrichments to ensure that the laboratory equipment was sterile and that aseptic laboratory techniques were being followed. One set of laboratory replicates was processed weekly on all growth media and enrichments to quantify method variability. If con-tamination was found in the laboratory blanks, either sample results were discarded or samples were rerun.
Standard quality-assurance and quality-control pro-cedures were followed for all PCR reactions (EPA, 2004). Detection limits for all PCR reactions were determined by using serial dilution of DNA from control organisms. For approximately every 20 samples of any given PCR assay, PCR positive controls (DNA extracted from bacteria known to con-tain the target gene) and PCR negative controls (no template reactions) were included.
Results of Microbiological AnalysesOf the 177 water samples collected, 12 samples were
omitted from the data analysis because of holding-time viola-tions and 64 of the samples were collected for the analysis of quality control. The 165 samples included in the analyses were assessed for occurrence and distribution of FIB during normal and high flows and for whether the samples exceeded the water quality criteria. These samples were also analyzed for specific pathogen genes by using PCR. Fecal indicator bacteria results are included in the USGS National Water Information System (NWIS) database.
Occurrence and Distribution of Fecal Indicator Bacteria
Fecal coliform concentrations ranged from < 2 to 950 colony-forming units per 100 mL (CFU/100 mL), E. coli concentrations ranged from < 2 to 26,000 CFU/100 mL, and enterococci concentrations ranged from < 2 to 31,000 CFU/100 mL. Fecal indicator bacteria concentrations for all samples are presented in appendix 1.
The lowest E. coli concentrations were recorded at the Au Sable River near Au Sable, MI (AU) (during high and normal flows), and the St. Joseph River at Niles, MI (during normal flow) (SJ). The highest E. coli concentrations were recorded at
Results of Microbiological Analyses 7
the River Rouge at Detroit, MI (during high flow) (RR). The lowest enterococci concentrations were recorded at the Au Sable River near Au Sable, MI (AU) (during high and normal flows), and the Oswego River at Lock 7 at Oswego, NY (OS) (during high flow). The highest enterococci concentrations were recorded at the River Rouge at Detroit, MI (RR) (during high flow). The lowest E. coli and enterococci concentrations were found at sites dominated by forest and agricultural land cover, whereas the highest E. coli and enterococci concentra-tions were recorded at sites dominated by urban development.
Enterococci and E. coli concentrations were evaluated on the basis of whether the data met or exceeded the 1986 EPA criterion for moderate full body contact recreation for freshwater for a single sample (Dufour and Ballantine, 1986). The moderate full body contact recreation criterion was
considered most applicable for this study given the type of recreation typically found on rivers; for example, kayaking, canoeing, and fishing. The moderate full body contact criterion for enterococci for a single sample is greater than or equal to 78 CFU/100 mL; and for E. coli, the recreation criterion is greater than or equal to 298 CFU/100 mL for a single sample. Of 112 samples analyzed for FIB concentrations, 21 percent of samples exceeded the EPA recreation criterion for E. coli, and 40 percent of samples exceeded the criterion for enterococci.
During high-flow events, 43 percent of all samples exceeded the EPA recreation criterion for E. coli, and 61 per-cent of samples exceeded the criterion for enterococci. During normal-flow conditions, about 2 percent of samples exceeded the criterion for E. coli, and about 21 percent of samples exceeded the criterion for enterococci.
Table 2. Growth media, target organisms, and incubation temperature requirements for the Great Lakes Restoration Initiative (GLRI) pathogens study.
[mL, milliliters; °C, degrees Celsius; E. coli, Escherichia coli]
Growth media Organism or methodVolume
filtered (mL)Incubation temperature and time
requirement
mFC Fecal coliform bacteria (E. coli, Shigella)
50 44.5 °C ± 0.5 °C for 22–24 hours
Modified mTEC E. coli 50, 10, 1 35–37 °C for 2 hours, then 44.5 °C ± 0.5 °C for 20–22 hours
mEI Enterococci 50, 10, 1 41 °C ± 0.5 °C for 22–24 hoursBolton Broth (BB) with Preston1
supplementCampylobacter 50 37 °C for 4 hours, then 42 °C
for 40–44 hoursGram Negative Broth (GN) Salmonella 50 37°C ± 1.0 °C for 22–24 hours
1Oxoid, Cambridge, United Kingdom.
Pathogen Gene target Virulence trait
E. coli eaeA AttachmentE. coli stx2 Severe toxinE. coli stx1 Moderate toxinE. coli rfbO157 Common outbreak strainShigella ipaH InvasionSalmonella invA InvasionSalmonella spvC Multiple virulence traitsCampylobacter jejuni and coli 16s rDNA (Campy) Pathogenic species marker
Table 3. Selected pathogen gene targets and virulence traits of the organism.
[E. coli, Escherichia coli]
8 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries
Occurrence and Distribution of Bacterial Pathogen Gene Markers
Data from the E. coli pathogen analysis showed that 68 percent of samples contained the eaeA gene, 20 percent of samples contained the stx2 gene, 12 percent of samples con-tained the stx1 gene, and 11 percent of samples contained the rfbO157 gene (fig. 3). Data from the Shigella analysis showed that 6 percent of samples contained the ipaH gene. Data from the Salmonella analysis showed that 7 percent of samples con-tained the invA gene and 14 percent of samples contained the spvC gene. Data from the Campylobacter analysis showed that 9 percent of samples contained the 16s rDNA gene (fig. 3).
Detections of bacterial pathogen gene markers by site and by sample are listed in appendix 3.
The frequency of pathogen gene markers detected in each sample is summarized in table 4. The greatest number of pathogen gene markers detected in any one sample was seven (River Rouge at Detroit, MI, during a May 26, 2011, high-flow event). This same May 26, 2011 sample from the River Rouge also contained the highest E. coli and enterococci concentra-tions of samples collected during this project (E. coli value of 26,000 CFU/100 mL; enterococci value, 31,000 CFU/100 mL).
0
10
20
30
40
50
60
70
80
eaeA stx2 stx1 rfb0157 ipaH invA spvC C. coli/C. jejuni
Posi
tive
sam
ples
, in
perc
ent
Gene marker
Figure 3. Frequency of samples testing positive for pathogen gene markers (C. coli, Campylobacter coli; C. jejuni, Campylobacter jejuni).
Figure 3. Frequency of samples testing positive for pathogen gene markers (C. coli, Campylobacter coli; C. jejuni, Campylobacter jejuni).
Table 4. Summary of the frequency of pathogen gene detections in a single sample.
[<, less than]
Flow conditions
Number of bacterial pathogen genes present
0 1 2 3 4 5 6 7 8
Percentage of samples in which the indicated number of genes were detected
High flow 10 12 13 2 3.5 6 0 1 0Normal flow 16 25 10 1 <1 0 0 0 0Total percent detection 26 37 23 3 4 6 0 1 0
Results of Microbiological Analyses 9
For those samples in which 3 or more genes were pres-ent, 14 of the 16 samples were collected during high-flow conditions.
Pathogen frequency was analyzed in relation to hydro-logic condition among all sites, as illustrated in figure 4. Overall, a higher percentage of samples tested positive for pathogens under high-flow conditions than during normal-flow conditions. For Campylobacter, the differences in the percent-age of samples that were positive for pathogens between high- and normal-flow conditions were less obvious. The invA gene for Salmonella was found only during high flows.
The frequencies of pathogen gene occurrence in samples that met and exceeded the EPA criteria for moderate full body contact recreation for E. coli and enterococci were compared for the 22 sites (table 5). Fisher’s Exact Test was run to deter-mine if there was a significant difference (p-value less than 0.05) between gene detection in samples that met or exceeded the water quality criteria. Overall, there was a greater occur-rence of pathogen gene markers in samples that exceeded the moderate full body contact recreation criteria for both E. coli and enterococci, the exception being a greater occurrence of the ipaH gene marker for Shigella in samples that met the criterion for E. coli.
0
10
20
30
40
50
60
70
80
eaeA stx2 stx1 rfb0157 ipaH invA spvC C. coli/C. jejuni
Perc
ent a
ge o
f sam
ples
Gene Marker
Percentage of normal-flow samples
Percentage of high-flow samples
Figure 4. Percentage of pathogen gene markers in relation to water quality criteria (C. coli, Campylobacter coli; C. jejuni, Campylobacter jejuni).
Table 5. Percentage of samples that tested positive for pathogenic gene markers during high-flow and normal-flow conditions.
[C. coli, Campylobacter coli; C. jejuni, Campylobacter jejuni, E. coli, Escherichia coli; n, number of samples; <, less than; nsd, no significant difference; p-value, p-value less than 0.05 = significant difference between groups, Fisher’s Exact Test]
Water quality criteria1 status
n eaeA stx2 stx1 rfb0157 ipaH invA spvCC. coli/C.
jejuni
Meet E. coli criterion 88 60 11 3 5 7 0 9 6Exceed E. coli criterion 24 96 50 42 33 4 33 33 21p-value — <0.05 <0.05 <0.05 <0.05 nsd <0.05 <0.05 <0.05
Meet enterococci criterion
67 54 10 5 3 6 0 3 2
Exceed enterococci criterion
45 91 33 22 22 7 18 31 20
p-value — <0.05 <0.05 <0.05 <0.05 nsd <0.05 <0.05 <0.051Water quality criteria = EPA Water Quality Criteria for Moderate Full Body Contact (Dufour and Ballantine, 1986).
10 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes Tributaries
Quality-Control ResultsTo assess for bias and precision, 21 field blanks, 21
source solution blanks, and 22 field replicates were collected and processed in the same manner as the regular field samples. All field blanks and source solution water blanks were nega-tive (no growth) for all FIB except for a sample collected at the River Raisin on August 30, 2011, which had an entero-cocci count of 2E (appendix 2). For PCR analysis, all no-tem-plate controls (negative controls) were found to be negative, and all positive assay controls yielded appropriate responses. However, the eaeA, rfb0157, and ipaH genes were infre-quently detected in the field blanks and source solution blanks, most likely as a result of contamination in the source solution blank water (appendix 4). There were two dates—Septem-ber 7, 2011, and August 24, 2011—for which environmental samples were collected in association with the source solution blank and field blank samples where there may have been possible contamination. The environmental sample, source solution blank, and field blank samples from these dates have been qualified with a “V” (analyte was detected in both the environmental sample and the associated blanks) as a result of possible contamination and data were not included in analyses (appendixes 3 and 4).
For all FIB field replicates, a relative standard deviation (RSD) was calculated and a mean RSD was computed (table 6) by using the formula below:
In all cases, the average RSD fell below the recom-mended 36 percent according to the initial and ongoing precision and recovery acceptance criteria that were used as a benchmark for replicate environmental samples (table 6) (EPA, 2009a).
For pathogen analysis, which yields only a presence or absence result, the frequencies of agreement between repli-cates were determined by dividing the number of paired repli-cates in agreement by the total number of replicates (table 7).
The field blank and source solution blank data results are presented in appendixes 2 and 4. All replicate data are presented in appendixes 1 and 3, along with the associated environmental sample.
SummaryA total of 177 environmental samples were collected at
USGS streamgaging stations during both normal-flow and high-flow conditions in 22 tributaries to the Great Lakes and were analyzed for the presence of FIB concentrations and to determine the occurrence of pathogen gene markers for Shigella species, Campylobacter jejuni and coli, Salmonella species, and pathogenic E. coli, including STEC. Results from a total of 165 samples were evaluated because 12 samples did not meet quality-control measures.
E. coli concentrations ranged from less than 2 to 26,000 CFU/100 mL. Enterococci concentrations ranged from less than 2 to 31,000 CFU/100 mL. Fecal coliform bacteria concentrations ranged from less than 2 to 950 CFU/100 ml. Data from E. coli pathogen analyses showed that 68 percent of samples contained the eaeA gene, 20 percent of samples contained the stx2 gene, 12 percent of samples contained the stx1 gene, and 11 percent of samples contained the rfbO157 gene. Data from the Shigella analysis showed that 6 percent of samples contained the ipaH gene. Data from the Salmonella analysis showed that 7 percent of samples contained the invA gene and 14 percent of samples contained the spvC gene. Data from the Campylobacter analysis showed that 9 percent of samples contained the 16S rDNA gene of Campylobacter coli and Campylobacter jejuni.
Table 6. Relative standard deviation of field replicates for quantitative microbial methods in the Great Lakes Restoration Initiative (GLRI) pathogens study.
[E. coli, Escherichia coli; RSD, relative standard deviation]
Statistic E. coli EnterococciFecal
coliforms
Average RSD, in percent 25.3 28.4 31.1Number of field replicates 22 22 22
Table 7. Frequency of agreement between field replicates for qualitative microbial methods in the Great Lakes Restoration Initiative (GLRI) pathogens study.
[C. coli, Campylobacter coli; C. jejuni, Campylobacter jejuni]
StatisticPathogen gene markers
eaeA stx2 stx1 rfb0157 ipaH invA spvC C. coli/C. jejuni
Percent agreement 82 95 95 82 100 95 91 95Number of field replicates 22 22 22 22 22 22 22 22
SX X X X X X
n=
− + − + − +
−
( ) ( ) ( ) ...1 2 3
1
2 2 2
References Cited 11
There were no samples in which all eight pathogen gene markers were detected; however, 88 percent of the samples that had three or more pathogen gene markers present were collected during high-flow conditions. Overall, there were a higher percentage of samples that tested positive for pathogens during high-flow conditions than normal-flow conditions, and there was a greater occurrence of pathogen gene markers in samples that exceeded the EPA moderate full body contact recreation criteria for E. coli and enterococci (Dufour, 1986) than in samples that met the EPA criteria; the exception was a greater occurrence of the ipaH gene marker for Shigella in samples that met the EPA criterion for E. coli than in samples that exceeded the EPA criterion for E. coli.
AcknowledgementsThis study was funded by the Great Lakes Restoration
Initiative. We wish to acknowledge the many USGS personnel from Indiana, Michigan, Minnesota, Ohio, New York and Wis-consin who collected the water samples for this project and communicated with the Michigan Bacteriological Research Laboratory.
References Cited
American Public Health Association, American Water Works Association, and Water Environment Federation, 1998, Standard methods for the examination of water and waste-water (20th ed.): Washington, D.C., American Public Health Association, p. 9–1 to 9–76.
Centers for Disease Control and Prevention (CDC), 2012a, Campylobacter: CDC Web page, accessed April 17, 2012, at http://www.cdc.gov/nczved/dfbmd/diseases/campylobacter/.
Centers for Disease Control and Prevention (CDC), 2012b, Recreational Water Illnesses (RWIs): CDC Web page, accessed April 17, 2012, at http://www.cdc.gov/healthywa-ter/swimming/rwi/.
Centers for Disease Control and Prevention (CDC), 2012c, Salmonella: CDC Web page, accessed April 17, 2012, at http://www.cdc.gov/salmonella.
Centers for Disease Control and Prevention (CDC), 2012d, STEC: CDC Web page, accessed April 17, 2012, at http://www.cdc.gov/ecoli/index.html.
Dufour, A.P., and Ballantine, R.K., 1986, Ambient water quality criteria for bacteria, 1986—Bacteriological ambient water quality criteria for marine and freshwater recreational waters: Washington, D.C., EPA 440/5–84–002.
Great Lakes Information Network (GLIN), 2013, Great Lakes facts and figures: GLIN Web page, accessed May 6, 2013, at http://www.glin.net/lakes/ref/lakefact.html.
Haack, S.K., Fogarty, L.R., Stelzer, E.A., Fuller, L.M, Bren-nan, A.K, Isaacs, N.M., and Johnson, H.E. 2013, Geo-graphic setting influences great lakes beach microbiological water quality: Environmental Science & Technology, v. 47, no. 21, p. 12054–12063.
Myers, D.N., Stoeckel, D.M., Bushon, R.N., Francy, D.S., and Brady, A.M.G., 2014, Fecal indicator bacteria (ver. 2.1): U.S. Geological Survey Techniques of Water-Resources Investigations, book 9, chap. A7, section 7.1, May 2014, accessed June 2014 at http://pubs.water.usgs.gov/twri9A/.
U.S. Environmental Protection Agency (EPA), 2004, Quality assurance/quality control guidance for laboratories per-forming PCR analysis on environmental samples: Office of Water, EPA 815-B-04-001, 56 p.
U.S. Environmental Protection Agency (EPA), 2009a, Method 1603 “Escherichia coli in water by membrane filtration using modified membrane-thermotolerant Escherichia coli agar”: Washington, D.C., EPA–821–R–09–007 [variously paged].
U.S. Environmental Protection Agency (EPA), 2009b, Method 1600 “Enterococci in water by membrane filtrations using membrane-Enterococcus indoxyl-β-D-glucoside agar”: Washington, D.C., EPA–821–R–09–016 [variously paged].
U.S. Environmental Protection Agency (EPA), 2012, Recre-ational water quality criteria: Office of Water, EPA 815–F–12–058, 63 p.
U.S. Environmental Protection Agency (EPA) and U.S. Geological Survey (USGS), 2012, National Hydrography Dataset Plus - NHDPlus version 2.1, accessed May 2012 at http://www.horizon-systems.com/NHDPlus/NHDPlusV2_home.php.
U.S. Geological Survey (USGS), 2006, Collection of water samples (ver. 2.0): U.S. Geological Survey Techniques of Water-Resources Investigations, book 9, chap. A4, Septem-ber 2006, accessed June 1, 2014, at http://pubs.water.usgs.gov/twri9A4/.
U.S. Geological Survey (USGS), 2011, National Land Cover Database (NLCD) 2006 Land Cover, accessed April 3, 2012, at http://www.mrlc.gov/nlcd06_data.php.
U.S. Geological Survey (USGS), Great Lakes Restoration Ini-tiative (GLRI), 2014, Forecast/nowcast Great Lakes nutrient and sediment loadings: USGS/GLRI Web page, accessed March 6, 2014, at http://cida.usgs.gov/glri/projects/near-shore_health/forecast_loadings.html.
Appendix 13
Appendixes
1. Fecal indicator bacteria concentrations in Great Lakes tributaries, 2011 ........................14 2. Quality-control data—Fecal indicator bacteria concentrations in Great Lakes
tributaries, 2011 ...........................................................................................................................20 3. Pathogen gene detection in Great Lakes tributaries, 2011 ..................................................22 4. Quality-control data—Pathogen gene detection in Great Lakes tributaries, 2011 .........28
14 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
1.
Feca
l ind
icat
or b
acte
ria c
once
ntra
tions
in G
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Appendix 15A
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16 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
1.
Feca
l ind
icat
or b
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ria c
once
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colif
orm
s(C
FU/
stat
ion
IDID
cond
ition
sty
peco
deco
de(C
FU/1
00 m
L)co
deda
tesa
mpl
e(C
FU/1
00m
L)10
0 m
L)
0415
7000
SG-0
13/
15/2
011
Nor
mal
Reg
ular
210
E66
160
E
0415
7000
SG-0
56/
16/2
011
Nor
mal
Reg
ular
150
E36
E42
0415
7000
SG-0
67/
14/2
011
Nor
mal
Reg
ular
950
E25
E12
E04
1570
00SG
-07
7/14
/201
1N
orm
alR
eplic
ate
SG-0
685
0E
20E
13E
0415
7000
SG-0
88/
23/2
011
Nor
mal
Reg
ular
5230
E12
E
0415
7000
SG-1
19/
14/2
011
Nor
mal
Reg
ular
110
6040
0410
1500
SJ-0
24/
7/20
11N
orm
alR
egul
ar26
E2
<7
E
0410
1500
SJ-0
77/
27/2
011
Nor
mal
Reg
ular
110
7452
0410
1500
SJ-0
88/
24/2
011
Nor
mal
Reg
ular
370
E13
052
0426
9000
SR-0
13/
24/2
011
Nor
mal
Reg
ular
16E
6E
2E
0426
9000
SR-0
44/
26/2
011
Nor
mal
Reg
ular
14E
8E
2E
0426
9000
SR-0
76/
21/2
011
Nor
mal
Reg
ular
nsns
ns
0426
9000
SR-0
87/
26/2
011
Nor
mal
Reg
ular
170
E13
046
0426
9000
SR-0
97/
26/2
011
Nor
mal
Rep
licat
eSR
-08
210
E14
052
0426
9000
SR-1
39/
20/2
011
Nor
mal
Reg
ular
150
E18
0E
110
0402
4000
ST-0
13/
15/2
011
Nor
mal
Reg
ular
8E
2E
2E
0402
4000
ST-0
24/
20/2
011
Nor
mal
Reg
ular
2E
4E
5E
0402
4000
ST-0
46/
14/2
011
Nor
mal
Reg
ular
12E
3E
2E
0402
4000
ST-0
56/
23/2
011
Nor
mal
Reg
ular
26E
18E
44E
0402
4000
ST-0
67/
21/2
011
Nor
mal
Reg
ular
120
26E
28E
0402
4000
ST-0
77/
21/2
011
Nor
mal
Rep
licat
eST
-06
110
4242
0402
4000
ST-1
18/
31/2
011
Nor
mal
Reg
ular
7440
20E
0402
4000
ST-1
29/
13/2
011
Nor
mal
Reg
ular
4225
E10
E
0413
7500
AU
-02
4/12
/201
1H
igh
Reg
ular
2<
2<
2<
0402
7000
BD
-01
4/11
/201
1H
igh
Reg
ular
110
82E
280
0402
7000
BD
-02
4/11
/201
1H
igh
Rep
licat
eB
D-0
114
0E
5627
0
Appendix 17A
ppen
dix
1.
Feca
l ind
icat
or b
acte
ria c
once
ntra
tions
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
-ta
l sam
ple;
E. c
oli,
Esch
eric
hia
coli;
CFU
/100
mL,
col
ony-
form
ing
units
per
100
mill
ilite
rs; n
s, no
sam
ple;
unc
, unc
ount
able
; E, e
stim
ated
val
ue; <
, les
s tha
n; >
, gre
ater
than
]
Sam
ple
A
ssoc
.Fe
cal
E. c
oli
USG
S
Fiel
d
Flow
Sa
mpl
e
Rem
ark
Rem
ark
Ente
roco
cci
Rem
ark
colle
ctio
n
envi
ron.
colif
orm
s(C
FU/
stat
ion
IDID
cond
ition
sty
peco
deco
de(C
FU/1
00 m
L)co
deda
tesa
mpl
e(C
FU/1
00m
L)10
0 m
L)
0402
7000
BD
-03
5/24
/201
1H
igh
Reg
ular
340
E51
015
0E
0409
5090
BN
-02
4/28
/201
1H
igh
Reg
ular
120
>14
00E
1100
E
0409
5090
BN
-03
5/25
/201
1H
igh
Reg
ular
610
E71
0E
350
0409
5090
BN
-04
6/8/
2011
Hig
hR
egul
ar46
17E
7E
0409
5090
BN
-10
9/7/
2011
Hig
hR
egul
ar94
4856
0416
5500
CL-
015/
16/2
011
Hig
hR
egul
ar12
0>
2500
3800
0416
5500
CL-
028/
17/2
011
Hig
hR
egul
ar23
0E
200
100
0416
5500
CL-
038/
17/2
011
Hig
hR
eplic
ate
CL-
0216
0E
140
84
0420
8000
CY-
014/
27/2
011
Hig
hR
egul
ar49
0E
590
250
0420
8000
CY-
027/
26/2
011
Hig
hR
egul
ar12
0>
180
100
0420
8000
CY-
037/
26/2
011
Hig
hR
eplic
ate
CY-
0212
0>
250
78
0420
8000
CY-
079/
20/2
011
Hig
hR
egul
ar12
0>
6100
8000
E
0420
8000
CY-
0810
/26/
2011
Hig
hR
egul
ar43
0E
430
420
0408
5138
5FX
-01
5/4/
2011
Hig
hR
egul
ar14
E64
4E
0411
9400
GR
-01
4/29
/201
1H
igh
Reg
ular
310
E29
028
0
0411
9400
GR
-02
5/18
/201
1H
igh
Reg
ular
140
E23
034
E
0411
9400
GR
-03
6/2/
2011
Hig
hR
egul
ar70
4817
E
0411
9400
GR
-04
6/29
/201
1H
igh
Reg
ular
240
E82
12E
0411
9400
GR
-05
6/29
/201
1H
igh
Rep
licat
eG
R-0
427
0E
808
E
0411
9400
GR
-06
8/2/
2011
Hig
hR
egul
ar13
0E
9017
E
0423
1600
GS-
024/
26/2
011
Hig
hR
egul
ar40
0E
320
270
0423
1600
GS-
035/
17/2
011
Hig
hR
egul
ar12
0>
1200
E14
00E
0423
1600
GS-
046/
2/20
11H
igh
Reg
ular
unc
390
120
0419
3500
MA
-01
3/8/
2011
Hig
hR
egul
ar57
0E
650
980
E
0408
5427
MN
-02
7/6/
2011
Hig
hR
egul
ar41
0E
7050
0408
7170
MW
-01
5/3/
2011
Hig
hR
egul
ar28
E58
27E
18 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
1.
Feca
l ind
icat
or b
acte
ria c
once
ntra
tions
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
-ta
l sam
ple;
E. c
oli,
Esch
eric
hia
coli;
CFU
/100
mL,
col
ony-
form
ing
units
per
100
mill
ilite
rs; n
s, no
sam
ple;
unc
, unc
ount
able
; E, e
stim
ated
val
ue; <
, les
s tha
n; >
, gre
ater
than
]
Sam
ple
A
ssoc
.Fe
cal
E. c
oli
USG
S
Fiel
d
Flow
Sa
mpl
e
Rem
ark
Rem
ark
Ente
roco
cci
Rem
ark
colle
ctio
n
envi
ron.
colif
orm
s(C
FU/
stat
ion
IDID
cond
ition
sty
peco
deco
de(C
FU/1
00 m
L)co
deda
tesa
mpl
e(C
FU/1
00m
L)10
0 m
L)
0404
0000
ON
-06
6/23
/201
1H
igh
Reg
ular
120
>92
0E
570
0424
9000
OS-
013/
9/20
11H
igh
Reg
ular
150
E10
064
0424
9000
OS-
034/
27/2
011
Hig
hR
egul
ar70
8866
0424
9000
OS-
045/
9/20
11H
igh
Reg
ular
4E
18E
2<
0424
9000
OS-
159/
7/20
11H
igh
Reg
ular
7015
E11
E
0419
5500
PO-0
13/
8/20
11H
igh
Reg
ular
580
E65
057
0
0419
5500
PO-0
24/
20/2
011
Hig
hR
egul
ar12
0>
1400
E36
0004
1955
00PO
-03
7/27
/201
1H
igh
Reg
ular
120
>24
031
0
0419
5500
PO-0
47/
27/2
011
Hig
hR
eplic
ate
PO-0
312
0>
220
280
0410
2500
PP-0
24/
21/2
011
Hig
hR
egul
ar12
0>
790
1200
E
0410
2500
PP-0
36/
1/20
11H
igh
Reg
ular
9610
072
0410
2500
PP-0
47/
19/2
011
Hig
hR
egul
ar12
0>
4800
6700
E
0410
2500
PP-0
58/
3/20
11H
igh
Reg
ular
410
E63
042
0E
0410
2500
PP-0
810
/4/2
011
Hig
hR
egul
ar12
070
82
0416
6500
RR
-01
5/16
/201
1H
igh
Reg
ular
120
>26
0057
00
0416
6500
RR
-02
5/26
/201
1H
igh
Reg
ular
120
>26
000
E31
000
E
0415
7000
SG-0
24/
6/20
11H
igh
Reg
ular
240
E22
044
0
0415
7000
SG-0
35/
2/20
11H
igh
Reg
ular
100
190
E98
0415
7000
SG-0
45/
16/2
011
Hig
hR
egul
ar12
0>
1200
E96
0E
0410
1500
SJ-0
13/
9/20
11H
igh
Reg
ular
unc
9644
0
0410
1500
SJ-0
34/
21/2
011
Hig
hR
egul
ar12
0>
860
E13
00E
0410
1500
SJ-0
44/
28/2
011
Hig
hR
egul
ar12
0>
1400
E87
0E
0410
1500
SJ-0
56/
28/2
011
Hig
hR
eplic
ate
SJ-0
626
0E
100
23
0410
1500
SJ-0
66/
28/2
011
Hig
hR
egul
ar38
0E
5840
0426
9000
SR-0
24/
6/20
11H
igh
Reg
ular
16E
5E
14E
0426
9000
SR-0
34/
12/2
011
Hig
hR
egul
ar50
40E
33E
Appendix 19A
ppen
dix
1.
Feca
l ind
icat
or b
acte
ria c
once
ntra
tions
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
-ta
l sam
ple;
E. c
oli,
Esch
eric
hia
coli;
CFU
/100
mL,
col
ony-
form
ing
units
per
100
mill
ilite
rs; n
s, no
sam
ple;
unc
, unc
ount
able
; E, e
stim
ated
val
ue; <
, les
s tha
n; >
, gre
ater
than
]
Sam
ple
A
ssoc
.Fe
cal
E. c
oli
USG
S
Fiel
d
Flow
Sa
mpl
e
Rem
ark
Rem
ark
Ente
roco
cci
Rem
ark
colle
ctio
n
envi
ron.
colif
orm
s(C
FU/
stat
ion
IDID
cond
ition
sty
peco
deco
de(C
FU/1
00 m
L)co
deda
tesa
mpl
e(C
FU/1
00m
L)10
0 m
L)
0426
9000
SR-0
55/
5/20
11H
igh
Reg
ular
24E
4617
E
0426
9000
SR-0
65/
24/2
011
Hig
hR
egul
ar30
E60
30E
0426
9000
SR-1
28/
23/2
011
Hig
hR
egul
ar22
0E
220
210
0402
4000
ST-0
35/
1/20
11H
igh
Reg
ular
16E
17E
6E
0402
4000
ST-1
08/
3/20
11H
igh
Reg
ular
580
E79
036
0
20 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
2.
Qual
ity-c
ontro
l dat
a—Fe
cal i
ndic
ator
bac
teria
con
cent
ratio
ns in
Gre
at L
akes
trib
utar
ies,
201
1.—
Cont
inue
d
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; C
FU/1
00 m
L, c
olon
y-fo
rmin
g un
its p
er 1
00 m
illili
ters
; E, e
stim
ated
val
ue; <
, les
s tha
n; >
, gre
ater
than
; N/A
; not
app
licab
le; n
s, no
sam
ple]
USG
S
stat
ion
IDFi
eld
ID
Sam
ple
co
llect
ion
da
teSa
mpl
e ty
peA
ssoc
. en
viro
n.
sam
ple
Feca
l co
lifor
ms
(CFU
/100
mL)
Rem
ark
code
E. c
oli
(CFU
/100
mL)
Rem
ark
code
Ente
ro-c
occi
(C
FU/1
00 m
L)Re
mar
k co
de
0413
7500
AU
-08
8/23
/201
1Fi
eld
blan
kA
U-0
72
<2
<2
<04
0270
00B
D-0
67/
12/2
011
Fiel
d bl
ank
BD
-04
2<
2<
2<
0409
5090
BN
-06
7/12
/201
1Fi
eld
blan
kB
N-0
52
<2
<2
<04
1655
00C
L-04
11/1
/201
1Fi
eld
blan
kns
2<
2<
2<
0420
8000
CY-
047/
26/2
011
Fiel
d bl
ank
CY-
022
<2
<2
<04
0851
385
FX-0
49/
19/2
011
Fiel
d bl
ank
ns2
<2
<2
<04
1194
00G
R-0
710
/31/
2011
Fiel
d bl
ank
ns2
<2
<2
<04
2316
00G
S-11
7/18
/201
1Fi
eld
blan
kG
S-09
2<
2<
2<
0419
3500
MA
-05
7/27
/201
1Fi
eld
blan
kM
A-0
32
<2
<2
<04
0675
00M
M-0
59/
7/20
11Fi
eld
blan
kM
M-0
32
<2
<2
<04
0854
27M
N-0
59/
8/20
11Fi
eld
blan
kM
N-0
32
<2
<2
<04
0871
70M
W-0
49/
20/2
011
Fiel
d bl
ank
MW
-02
2<
2<
2<
0404
0000
ON
-12
9/20
/201
1Fi
eld
blan
kns
2<
2<
2<
0424
9000
OS-
127/
18/2
011
Fiel
d bl
ank
OS-
102
<2
<2
<04
1955
00PO
-05
7/27
/201
1Fi
eld
blan
kPO
-03
2<
2<
2<
0416
6500
RR
-05
10/3
1/20
11Fi
eld
blan
kns
2<
2<
2<
0417
6500
RS-
048/
30/2
011
Fiel
d bl
ank
ns2
<2
<2
E04
1570
00SG
-09
8/23
/201
1Fi
eld
blan
kSG
-08
2<
2<
2<
0410
1500
SJ-0
98/
24/2
011
Fiel
d bl
ank
SJ-0
82
<2
<2
<04
2690
00SR
-10
7/26
/201
1Fi
eld
blan
kSR
-08
2<
2<
2<
0402
4000
ST-0
87/
21/2
011
Fiel
d bl
ank
ST-0
62
<2
<2
<04
1375
00A
U-0
98/
22/2
011
Sour
ce so
lutio
n bl
ank
ns2
<2
<2
<04
0270
00B
D-0
77/
12/2
011
Sour
ce so
lutio
n bl
ank
BD
-04
2<
2<
2<
0409
5090
BN
-07
7/12
/201
1So
urce
solu
tion
blan
kB
N-0
52
<2
<2
<04
1655
00C
L-05
11/1
/201
1So
urce
solu
tion
blan
kns
2<
2<
2<
0420
8000
CY-
057/
26/2
011
Sour
ce so
lutio
n bl
ank
CY-
022
<2
<2
<
Appendix 21A
ppen
dix
2.
Qual
ity-c
ontro
l dat
a—Fe
cal i
ndic
ator
bac
teria
con
cent
ratio
ns in
Gre
at L
akes
trib
utar
ies,
201
1.—
Cont
inue
d
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; C
FU/1
00 m
L, c
olon
y-fo
rmin
g un
its p
er 1
00 m
illili
ters
; E, e
stim
ated
val
ue; <
, les
s tha
n; >
, gre
ater
than
; N/A
; not
app
licab
le; n
s, no
sam
ple]
Sam
ple
A
ssoc
. Fe
cal
USG
S
Fiel
d
Rem
ark
E. c
oli
Rem
ark
Ente
ro-c
occi
Re
mar
k co
llect
ion
Sa
mpl
e ty
peen
viro
n.
colif
orm
s st
atio
n ID
IDco
de(C
FU/1
00 m
L)co
de(C
FU/1
00 m
L)co
deda
tesa
mpl
e(C
FU/1
00 m
L)
0408
5138
5FX
-05
9/19
/201
1So
urce
solu
tion
blan
kns
2<
2<
2<
0411
9400
GR
-08
10/3
1/20
11So
urce
solu
tion
blan
kns
2<
2<
2<
0423
1600
GS-
127/
18/2
011
Sour
ce so
lutio
n bl
ank
GS-
092
<2
<2
<04
1935
00M
A-0
67/
27/2
011
Sour
ce so
lutio
n bl
ank
MA
-03
2<
2<
2<
0406
7500
MM
-06
9/19
/201
1So
urce
solu
tion
blan
kns
2<
2<
2<
0408
5427
MN
-06
9/19
/201
1So
urce
solu
tion
blan
kns
2<
2<
2<
0408
7170
MW
-05
9/20
/201
1So
urce
solu
tion
blan
kM
W-0
22
<2
<2
<04
0400
00O
N-1
19/
20/2
011
Sour
ce so
lutio
n bl
ank
ns2
<2
<2
<04
2490
00O
S-13
7/18
/201
1So
urce
solu
tion
blan
kO
S-10
2<
2<
2<
0419
5500
PO-0
67/
27/2
011
Sour
ce so
lutio
n bl
ank
PO-0
32
<2
<2
<04
1665
00R
R-0
610
/31/
2011
Sour
ce so
lutio
n bl
ank
ns2
<2
<2
<04
1765
00R
S-05
8/30
/201
1So
urce
solu
tion
blan
kns
2<
2<
2<
0415
7000
SG-1
08/
23/2
011
Sour
ce so
lutio
n bl
ank
SG-0
82
<2
<2
<04
1015
00SJ
-10
8/24
/201
1So
urce
solu
tion
blan
kSJ
-08
2<
2<
2<
0426
9000
SR-1
17/
26/2
011
Sour
ce so
lutio
n bl
ank
SR-0
82
<2
<2
<04
0240
00ST
-09
7/21
/201
1So
urce
solu
tion
blan
kST
-06
2<
2<
2<
22 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
3.
Path
ogen
gen
e de
tect
ion
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; +
, gen
e pr
esen
t in
sam
ple;
—, g
ene
abse
nt in
sam
ple;
ns,
no sa
mpl
e; V
– re
mar
k co
de in
dica
ting
poss
ible
con
tam
inat
ion
(ana
lyte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
USG
S
stat
ion
IDFi
eld
ID
Sam
ple
co
llect
ion
da
te
Flow
co
nditi
ons
Sam
ple
type
Ass
oc.
e
nvir
on.
sam
ple
E. c
oli g
ene
data
Shig
ella
ge
ne d
ata
Salm
onel
la
gene
dat
aCa
mpy
loba
cter
ge
ne d
ata
eaeA
stx2
stx1
rfb
O
157
ipaH
invA
spvC
C. c
oli/
C. je
juni
0413
7500
AU
-01
3/15
/201
1N
orm
alR
egul
ar —
——
——
——
—04
1375
00A
U-0
46/
15/2
011
Nor
mal
Reg
ular
——
——
——
——
0413
7500
AU
-05
7/13
/201
1N
orm
alR
egul
ar+
——
——
——
—04
1375
00A
U-0
67/
13/2
011
Nor
mal
Rep
licat
eA
U-0
5+
——
——
——
—
0413
7500
AU
-07
8/23
/201
1N
orm
alR
egul
ar—
——
—+
——
—04
1375
00A
U-1
09/
13/2
011
Nor
mal
Reg
ular
——
——
——
——
0402
7000
BD
-04
7/12
/201
1N
orm
alR
egul
ar+
——
——
——
—04
0270
00B
D-0
57/
12/2
011
Nor
mal
Rep
licat
eB
-04
+—
——
——
——
0402
7000
BD
-08
8/16
/201
1N
orm
alR
egul
ar+
——
——
——
—04
0270
00B
D-0
99/
20/2
011
Nor
mal
Reg
ular
+—
——
——
+—
0409
5090
BN
-01
3/30
/201
1N
orm
alR
egul
ar+
——
——
——
—04
0950
90B
N-0
57/
12/2
011
Nor
mal
Reg
ular
+—
——
——
+—
0409
5090
BN
-08
8/11
/201
1N
orm
alR
egul
ar+
——
——
——
—04
0950
90B
N-0
98/
11/2
011
Nor
mal
Rep
licat
eB
N-0
8+
——
——
——
—
0420
8000
CY-
068/
31/2
011
Nor
mal
Reg
ular
+—
——
——
—+
0408
5138
5FX
-02
8/16
/201
1N
orm
alR
egul
ar—
——
——
——
—04
0851
385
FX-0
38/
16/2
011
Nor
mal
Rep
licat
eFX
-02
——
——
——
——
0423
1600
GS-
014/
5/20
11N
orm
alR
egul
ar+
——
——
——
+04
2316
00G
S-09
7/18
/201
1N
orm
alR
egul
ar—
——
——
——
—04
2316
00G
S-10
7/18
/201
1N
orm
alR
eplic
ate
GS-
09—
——
——
+—
—
0423
1600
GS-
138/
8/20
11N
orm
alR
egul
ar—
——
——
——
—04
1935
00M
A-0
24/
19/2
011
Nor
mal
Reg
ular
+—
——
——
——
0419
3500
MA
-03
7/27
/201
1N
orm
alR
egul
ar+
——
+—
——
—04
1935
00M
A-0
47/
27/2
011
Nor
mal
Rep
licat
eM
A-0
3+
——
+—
——
—
0406
7500
MM
-02
7/7/
2011
Nor
mal
Reg
ular
——
——
——
——
Appendix 23A
ppen
dix
3.
Path
ogen
gen
e de
tect
ion
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; +
, gen
e pr
esen
t in
sam
ple;
—, g
ene
abse
nt in
sam
ple;
ns,
no sa
mpl
e; V
– re
mar
k co
de in
dica
ting
poss
ible
con
tam
inat
ion
(ana
lyte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
Shig
ella
Sa
lmon
ella
Ca
mpy
loba
cter
E.
col
i gen
e da
taSa
mpl
e
Ass
oc.
ge
ne d
ata
gene
dat
age
ne d
ata
USG
S
Fiel
d
Flow
co
llect
ion
Sa
mpl
e ty
pe e
nvir
on.
stat
ion
IDID
cond
ition
sda
te s
ampl
erf
b
C. c
oli/
eaeA
stx2
stx1
ipaH
invA
spvC
O15
7C.
jeju
ni
0406
7500
MM
-03
9/7/
2011
Nor
mal
Reg
ular
+V—
——
——
——
0406
7500
MM
-04
9/7/
2011
Nor
mal
Rep
licat
eM
M-0
3+
——
+—
——
—
0408
5427
MN
-03
9/8/
2011
Nor
mal
Reg
ular
——
——
——
—+
0408
5427
MN
-04
9/8/
2011
Nor
mal
Rep
licat
eM
N-0
3+
——
——
——
+
0408
7170
MW
-02
9/20
/201
1N
orm
alR
egul
ar+
——
+—
——
—04
0871
70M
W-0
39/
20/2
011
Nor
mal
Rep
licat
eM
W-0
2+
——
——
+—
—
0404
0000
ON
-01
3/23
/201
1N
orm
alR
egul
ar—
—+
——
——
—04
0400
00O
N-0
24/
5/20
11N
orm
alR
egul
ar+
——
——
——
—04
0400
00O
N-0
34/
26/2
011
Nor
mal
Reg
ular
——
——
——
——
0404
0000
ON
-04
5/25
/201
1N
orm
alR
egul
ar+
——
——
——
—04
0400
00O
N-0
56/
6/20
11N
orm
alR
egul
ar+
——
——
——
—04
0400
00O
N-0
77/
14/2
011
Nor
mal
Reg
ular
——
——
——
——
0404
0000
ON
-08
8/17
/201
1N
orm
alR
egul
ar—
——
—+
——
—04
0400
00O
N-0
99/
13/2
011
Nor
mal
Reg
ular
+—
——
——
——
0404
0000
ON
-10
9/13
/201
1N
orm
alR
eplic
ate
ON
-09
+—
——
——
——
0424
9000
OS-
024/
7/20
11N
orm
alR
egul
ar—
——
——
——
—04
2490
00O
S-05
6/8/
2011
Nor
mal
Reg
ular
+—
——
——
——
0424
9000
OS-
107/
18/2
011
Nor
mal
Reg
ular
——
——
——
——
0424
9000
OS-
117/
18/2
011
Nor
mal
Rep
licat
eO
S-10
+—
——
——
——
0424
9000
OS-
148/
8/20
11N
orm
alR
egul
ar+
——
——
——
—04
1025
00PP
-01
4/11
/201
1N
orm
alR
egul
ar+
+—
——
——
—04
1025
00PP
-06
9/8/
2011
Nor
mal
Reg
ular
++
——
——
++
0416
6500
RR
-03
8/17
/201
1N
orm
alR
egul
ar+
——
+—
—+
—04
1665
00R
R-0
48/
17/2
011
Nor
mal
Rep
licat
eR
R-0
3+
——
——
—+
+
0417
6500
RS-
016/
16/2
011
Nor
mal
Reg
ular
++
——
——
——
24 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
3.
Path
ogen
gen
e de
tect
ion
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; +
, gen
e pr
esen
t in
sam
ple;
—, g
ene
abse
nt in
sam
ple;
ns,
no sa
mpl
e; V
– re
mar
k co
de in
dica
ting
poss
ible
con
tam
inat
ion
(ana
lyte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
Shig
ella
Sa
lmon
ella
Ca
mpy
loba
cter
E.
col
i gen
e da
taSa
mpl
e
Ass
oc.
ge
ne d
ata
gene
dat
age
ne d
ata
USG
S
Fiel
d
Flow
co
llect
ion
Sa
mpl
e ty
pe e
nvir
on.
stat
ion
IDID
cond
ition
sda
te s
ampl
erf
b
C. c
oli/
eaeA
stx2
stx1
ipaH
invA
spvC
O15
7C.
jeju
ni
0417
6500
RS-
028/
23/2
011
Nor
mal
Reg
ular
+—
——
+—
——
0417
6500
RS-
038/
23/2
011
Nor
mal
Rep
licat
eR
S-02
+—
——
+—
——
0415
7000
SG-0
13/
15/2
011
Nor
mal
Reg
ular
+—
——
——
——
0415
7000
SG-0
56/
16/2
011
Nor
mal
Reg
ular
——
——
——
——
0415
7000
SG-0
67/
14/2
011
Nor
mal
Reg
ular
——
——
——
——
0415
7000
SG-0
77/
14/2
011
Nor
mal
Rep
licat
eSG
-06
+—
——
——
——
0415
7000
SG-0
88/
23/2
011
Nor
mal
Reg
ular
+—
——
——
——
0415
7000
SG-1
19/
14/2
011
Nor
mal
Reg
ular
+—
——
——
——
0410
1500
SJ-0
24/
7/20
11N
orm
alR
egul
ar—
——
——
——
—04
1015
00SJ
-07
7/27
/201
1N
orm
alR
egul
ar+
——
——
——
—04
1015
00SJ
-08
8/24
/201
1N
orm
alR
egul
ar+V
——
——
——
—04
2690
00SR
-01
3/24
/201
1N
orm
alR
egul
ar—
—+
——
——
—04
2690
00SR
-04
4/26
/201
1N
orm
alR
egul
ar—
——
——
——
—04
2690
00SR
-07
6/21
/201
1N
orm
alR
egul
ar+
——
——
——
—04
2690
00SR
-08
7/26
/201
1N
orm
alR
egul
ar+
——
——
——
—04
2690
00SR
-09
7/26
/201
1N
orm
alR
eplic
ate
SR-0
8+
——
——
——
—
0426
9000
SR-1
39/
20/2
011
Nor
mal
Reg
ular
+—
——
——
+—
0402
4000
ST-0
13/
15/2
011
Nor
mal
Reg
ular
——
——
——
——
0402
4000
ST-0
24/
20/2
011
Nor
mal
Reg
ular
——
——
——
——
0402
4000
ST-0
46/
14/2
011
Nor
mal
Reg
ular
++
——
——
——
0402
4000
ST-0
56/
23/2
011
Nor
mal
Reg
ular
+—
——
——
——
0402
4000
ST-0
67/
21/2
011
Nor
mal
Reg
ular
——
——
——
——
0402
4000
ST-0
77/
21/2
011
Nor
mal
Rep
licat
eST
-06
+—
——
——
——
0402
4000
ST-1
18/
31/2
011
Nor
mal
Reg
ular
——
——
——
—+
0402
4000
ST-1
29/
13/2
011
Nor
mal
Reg
ular
+—
——
——
——
Appendix 25A
ppen
dix
3.
Path
ogen
gen
e de
tect
ion
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; +
, gen
e pr
esen
t in
sam
ple;
—, g
ene
abse
nt in
sam
ple;
ns,
no sa
mpl
e; V
– re
mar
k co
de in
dica
ting
poss
ible
con
tam
inat
ion
(ana
lyte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
Shig
ella
Sa
lmon
ella
Ca
mpy
loba
cter
E.
col
i gen
e da
taSa
mpl
e
Ass
oc.
ge
ne d
ata
gene
dat
age
ne d
ata
USG
S
Fiel
d
Flow
co
llect
ion
Sa
mpl
e ty
pe e
nvir
on.
stat
ion
IDID
cond
ition
sda
te s
ampl
erf
b
C. c
oli/
eaeA
stx2
stx1
ipaH
invA
spvC
O15
7C.
jeju
ni
0413
7500
AU
-02
4/12
/201
1H
igh
Reg
ular
——
——
——
——
0402
7000
BD
-01
4/11
/201
1H
igh
Reg
ular
——
——
——
——
0402
7000
BD
-02
4/11
/201
1H
igh
Rep
licat
eB
D-0
1—
——
——
——
—
0402
7000
BD
-03
5/24
/201
1H
igh
Reg
ular
+—
——
——
——
0409
5090
BN
-02
4/28
/201
1H
igh
Reg
ular
+—
++
—+
—+
0409
5090
BN
-03
5/25
/201
1H
igh
Reg
ular
+—
——
—+
——
0409
5090
BN
-04
6/8/
2011
Hig
hR
egul
ar—
——
——
——
—04
0950
90B
N-1
09/
7/20
11H
igh
Reg
ular
+—
——
——
——
0416
5500
CL-
015/
16/2
011
Hig
hR
egul
ar+
++
+—
—+
—04
1655
00C
L-02
8/17
/201
1H
igh
Reg
ular
+—
——
——
+—
0416
5500
CL-
038/
17/2
011
Hig
hR
eplic
ate
CL-
02+
——
+—
—+
—
0420
8000
CY-
014/
27/2
011
Hig
hR
egul
ar—
——
——
——
—04
2080
00C
Y-02
7/26
/201
1H
igh
Reg
ular
+—
——
——
——
0420
8000
CY-
037/
26/2
011
Hig
hR
eplic
ate
CY-
02+
+—
——
——
—
0420
8000
CY-
079/
20/2
011
Hig
hR
egul
ar+
++
+—
—+
—04
2080
00C
Y-08
10/2
6/20
11H
igh
Reg
ular
+—
——
——
——
0408
5138
5FX
-01
5/4/
2011
Hig
hR
egul
ar+
——
——
——
—04
1194
00G
R-0
14/
29/2
011
Hig
hR
egul
ar+
+—
——
——
—04
1194
00G
R-0
25/
18/2
011
Hig
hR
egul
ar+
——
——
——
—04
1194
00G
R-0
36/
2/20
11H
igh
Reg
ular
+—
——
+—
——
0411
9400
GR
-04
6/29
/201
1H
igh
Reg
ular
+—
——
——
+—
0411
9400
GR
-05
6/29
/201
1H
igh
Rep
licat
eG
R-0
4+
—+
——
——
—
0411
9400
GR
-06
8/2/
2011
Hig
hR
egul
ar+
++
—+
——
—04
2316
00G
S-02
4/26
/201
1H
igh
Reg
ular
+—
+—
——
——
0423
1600
GS-
035/
17/2
011
Hig
hR
egul
ar+
—+
+—
——
—
26 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
3.
Path
ogen
gen
e de
tect
ion
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; +
, gen
e pr
esen
t in
sam
ple;
—, g
ene
abse
nt in
sam
ple;
ns,
no sa
mpl
e; V
– re
mar
k co
de in
dica
ting
poss
ible
con
tam
inat
ion
(ana
lyte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
Shig
ella
Sa
lmon
ella
Ca
mpy
loba
cter
E.
col
i gen
e da
taSa
mpl
e
Ass
oc.
ge
ne d
ata
gene
dat
age
ne d
ata
USG
S
Fiel
d
Flow
co
llect
ion
Sa
mpl
e ty
pe e
nvir
on.
stat
ion
IDID
cond
ition
sda
te s
ampl
erf
b
C. c
oli/
eaeA
stx2
stx1
ipaH
invA
spvC
O15
7C.
jeju
ni
0423
1600
GS-
046/
2/20
11H
igh
Reg
ular
++
——
——
——
0419
3500
MA
-01
3/8/
2011
Hig
hR
egul
ar+
+—
——
++
+04
0854
27M
N-0
27/
6/20
11H
igh
Reg
ular
+—
——
——
——
0408
7170
MW
-01
5/3/
2011
Hig
hR
egul
ar—
——
——
——
—04
0400
00O
N-0
66/
23/2
011
Hig
hR
egul
ar+
——
+—
——
—04
2490
00O
S-01
3/9/
2011
Hig
hR
egul
ar—
——
——
——
—04
2490
00O
S-03
4/27
/201
1H
igh
Reg
ular
—+
——
——
——
0424
9000
OS-
045/
9/20
11H
igh
Reg
ular
——
——
——
——
0424
9000
OS-
159/
7/20
11H
igh
Reg
ular
+—
——
——
——
0419
5500
PO-0
13/
8/20
11H
igh
Reg
ular
+—
——
——
—+
0419
5500
PO-0
24/
20/2
011
Hig
hR
egul
ar+
+—
+—
+—
—04
1955
00PO
-03
7/27
/201
1H
igh
Reg
ular
+—
——
——
——
0419
5500
PO-0
47/
27/2
011
Hig
hR
eplic
ate
PO-0
3+
——
——
——
—
0410
2500
PP-0
24/
21/2
011
Hig
hR
egul
ar+
+—
——
++
+04
1025
00PP
-03
6/1/
2011
Hig
hR
egul
ar+
+—
——
nsns
—04
1025
00PP
-04
7/19
/201
1H
igh
Reg
ular
++
+—
—+
+—
0410
2500
PP-0
58/
3/20
11H
igh
Reg
ular
++
——
——
——
0410
2500
PP-0
810
/4/2
011
Hig
hR
egul
ar+
——
——
——
—04
1665
00R
R-0
15/
16/2
011
Hig
hR
egul
ar+
++
——
—+
—04
1665
00R
R-0
25/
26/2
011
Hig
hR
egul
ar+
++
++
++
—04
1570
00SG
-02
4/6/
2011
Hig
hR
egul
ar+
——
+—
——
—04
1570
00SG
-03
5/2/
2011
Hig
hR
egul
ar+
——
——
——
—04
1570
00SG
-04
5/16
/201
1H
igh
Reg
ular
++
——
——
+—
0410
1500
SJ-0
13/
9/20
11H
igh
Reg
ular
+—
——
——
—+
0410
1500
SJ-0
34/
21/2
011
Hig
hR
egul
ar+
++
+—
+—
—
Appendix 27A
ppen
dix
3.
Path
ogen
gen
e de
tect
ion
in G
reat
Lak
es tr
ibut
arie
s, 2
011.
—Co
ntin
ued
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e; E
. col
i, Es
cher
ichi
a co
li; +
, gen
e pr
esen
t in
sam
ple;
—, g
ene
abse
nt in
sam
ple;
ns,
no sa
mpl
e; V
– re
mar
k co
de in
dica
ting
poss
ible
con
tam
inat
ion
(ana
lyte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
Shig
ella
Sa
lmon
ella
Ca
mpy
loba
cter
E.
col
i gen
e da
taSa
mpl
e
Ass
oc.
ge
ne d
ata
gene
dat
age
ne d
ata
USG
S
Fiel
d
Flow
co
llect
ion
Sa
mpl
e ty
pe e
nvir
on.
stat
ion
IDID
cond
ition
sda
te s
ampl
erf
b
C. c
oli/
eaeA
stx2
stx1
ipaH
invA
spvC
O15
7C.
jeju
ni
0410
1500
SJ-0
44/
28/2
011
Hig
hR
egul
ar+
—+
——
——
—04
1015
00SJ
-05
6/28
/201
1H
igh
Rep
licat
eSJ
—06
++
——
——
——
0410
1500
SJ-0
66/
28/2
011
Hig
hR
egul
ar+
+—
——
——
—04
2690
00SR
-02
4/6/
2011
Hig
hR
egul
ar+
——
——
——
—04
2690
00SR
-03
4/12
/201
1H
igh
Reg
ular
——
——
——
——
0426
9000
SR-0
55/
5/20
11H
igh
Reg
ular
——
——
——
——
0426
9000
SR-0
65/
24/2
011
Hig
hR
egul
ar—
——
——
——
—04
2690
00SR
-12
8/23
/201
1H
igh
Reg
ular
++
——
+—
+—
0402
4000
ST-0
35/
1/20
11H
igh
Reg
ular
——
——
——
——
0402
4000
ST-1
08/
3/20
11H
igh
Reg
ular
+—
——
——
——
28 Fecal Indicator Bacteria and Gene Markers of Pathogenic Bacteria in Great Lakes TributariesA
ppen
dix
4.
Qual
ity-c
ontro
l dat
a—Pa
thog
en g
ene
dete
ctio
n in
Gre
at L
akes
trib
utar
ies,
201
1.—
Cont
inue
d
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e;
E. c
oli,
Esch
eric
hia
coli;
+, g
ene
pres
ent i
n sa
mpl
e; -
, gen
e ab
sent
in sa
mpl
e; n
s, no
sam
ple;
v –
val
ue q
ualifi
er c
ode
(ana
lyte
det
ecte
d in
labo
rato
ry b
lank
); V
– v
alue
qua
lifier
cod
e (c
onta
min
atio
n,
anal
yte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
USGS
stat
ion
IDFi
eld ID
Sam
ple
colle
ctio
n
Date
Sam
ple t
ype
Ass
oc.
e
nviro
n.
sam
ple
E. co
li gen
e dat
aSh
igell
a ge
ne
data
Salm
onell
a ge
ne
data
Cam
pylo
bact
er
gene
da
ta
eaeA
stx2
stx1
rfb O157
ipaH
invA
spvC
C. co
li/C.
jeju
ni04
1375
00A
U-0
88/
23/2
011
Fiel
d bl
ank
AU
-07
——
——
——
——
0402
7000
BD
-06
7/12
/201
1Fi
eld
blan
kB
D-0
4—
——
——
——
—04
0950
90B
N-0
67/
12/2
011
Fiel
d bl
ank
BN
-05
——
——
——
——
0416
5500
CL-
0411
/1/2
011
Fiel
d bl
ank
ns—
——
——
——
—04
2080
00C
Y-04
7/26
/201
1Fi
eld
blan
kC
Y-02
——
——
——
——
0408
5138
5FX
-04
9/19
/201
1Fi
eld
blan
kns
+v—
——
——
——
0411
9400
GR
-07
10/3
1/20
11Fi
eld
blan
kns
——
——
+v—
——
0423
1600
GS-
117/
18/2
011
Fiel
d bl
ank
GS-
09—
——
——
——
—04
1935
00M
A-0
57/
27/2
011
Fiel
d bl
ank
MA
-03
——
——
——
——
0406
7500
MM
-05
9/7/
2011
Fiel
d bl
ank
MM
-03
+V—
—+V
——
——
0408
5427
MN
-05
9/8/
2011
Fiel
d bl
ank
MN
-03
——
——
——
——
0408
7170
MW
-04
9/20
/201
1Fi
eld
blan
kM
W-0
2—
——
——
——
—04
0400
00O
N-1
29/
20/2
011
Fiel
d bl
ank
ns—
——
——
——
—04
2490
00O
S-12
7/18
/201
1Fi
eld
blan
kO
S-10
——
——
——
——
0419
5500
PO-0
57/
27/2
011
Fiel
d bl
ank
PO-0
3—
——
——
——
—04
1665
00R
R-0
510
/31/
2011
Fiel
d bl
ank
ns+v
——
——
——
—04
1765
00R
S-04
8/30
/201
1Fi
eld
blan
kns
——
——
+v—
——
0415
7000
SG-0
98/
23/2
011
Fiel
d bl
ank
SG-0
8—
——
——
——
—04
1015
00SJ
-09
8/24
/201
1Fi
eld
blan
kSJ
-08
——
——
——
——
0426
9000
SR-1
07/
26/2
011
Fiel
d bl
ank
SR-0
8—
——
——
——
—04
0240
00ST
-08
7/21
/201
1Fi
eld
blan
kST
-06
——
——
——
——
0413
7500
AU
-09
8/22
/201
1So
urce
solu
tion
blan
kns
——
——
+v—
——
0402
7000
BD
-07
7/12
/201
1So
urce
solu
tion
blan
kB
D-0
4—
——
——
——
—04
0950
90B
N-0
77/
12/2
011
Sour
ce so
lutio
n bl
ank
BN
-05
——
——
——
——
0416
5500
CL-
0511
/1/2
011
Sour
ce so
lutio
n bl
ank
ns—
——
——
——
—04
2080
00C
Y-05
7/26
/201
1So
urce
solu
tion
blan
kC
Y-02
——
——
——
——
Appendix 29A
ppen
dix
4.
Qual
ity-c
ontro
l dat
a—Pa
thog
en g
ene
dete
ctio
n in
Gre
at L
akes
trib
utar
ies,
201
1.—
Cont
inue
d
[Stre
amga
ging
stat
ions
cor
resp
ondi
ng to
stat
ion
IDs a
nd fi
eld
IDs a
re li
sted
in ta
ble
1 in
the
mai
n re
port.
USG
S, U
.S. G
eolo
gica
l Sur
vey;
Ass
oc. e
nviro
n. sa
mpl
e, a
ssoc
iate
d en
viro
nmen
tal s
ampl
e;
E. c
oli,
Esch
eric
hia
coli;
+, g
ene
pres
ent i
n sa
mpl
e; -
, gen
e ab
sent
in sa
mpl
e; n
s, no
sam
ple;
v –
val
ue q
ualifi
er c
ode
(ana
lyte
det
ecte
d in
labo
rato
ry b
lank
); V
– v
alue
qua
lifier
cod
e (c
onta
min
atio
n,
anal
yte
was
det
ecte
d in
bot
h th
e en
viro
nmen
tal s
ampl
e an
d th
e as
soci
ated
bla
nks)
]
Shig
ella
Salm
onell
a Ca
mpy
loba
cter
E.
coli g
ene d
ata
gene
ge
ne
gene
Sa
mpl
e A
ssoc
.
USGS
stat
ion
data
data
data
Field
IDco
llect
ion
Sa
mpl
e typ
e e
nviro
n.
IDDa
te sa
mpl
erfb
C. co
li/ea
eAst
x2st
x1ip
aHin
vAsp
vCO1
57C.
jeju
ni04
0851
385
FX-0
59/
19/2
011
Sour
ce so
lutio
n bl
ank
ns—
——
——
——
—04
1194
00G
R-0
810
/31/
2011
Sour
ce so
lutio
n bl
ank
ns+v
——
——
——
—04
2316
00G
S-12
7/18
/201
1So
urce
solu
tion
blan
kG
S-09
——
——
——
——
0419
3500
MA
-06
7/27
/201
1So
urce
solu
tion
blan
kM
A-0
3—
——
——
——
—04
0675
00M
M-0
69/
19/2
011
Sour
ce so
lutio
n bl
ank
ns—
——
——
——
—04
0854
27M
N-0
69/
19/2
011
Sour
ce so
lutio
n bl
ank
ns—
——
——
——
—04
0871
70M
W-0
59/
20/2
011
Sour
ce so
lutio
n bl
ank
MW
-02
——
——
——
——
0404
0000
ON
-11
9/20
/201
1So
urce
solu
tion
blan
kns
+v—
——
——
——
0424
9000
OS-
137/
18/2
011
Sour
ce so
lutio
n bl
ank
OS-
10—
——
——
——
—04
1955
00PO
-06
7/27
/201
1So
urce
solu
tion
blan
kPO
-03
——
——
——
——
0416
6500
RR
-06
10/3
1/20
11So
urce
solu
tion
blan
kns
——
——
——
——
0417
6500
RS-
058/
30/2
011
Sour
ce so
lutio
n bl
ank
ns—
——
——
——
—04
1570
00SG
-10
8/23
/201
1So
urce
solu
tion
blan
kSG
-08
——
——
——
——
0410
1500
SJ-1
08/
24/2
011
Sour
ce so
lutio
n bl
ank
SJ-0
8+V
——
——
——
—04
2690
00SR
-11
7/26
/201
1So
urce
solu
tion
blan
kSR
-08
——
——
——
——
0402
4000
ST-0
97/
21/2
011
Sour
ce so
lutio
n bl
ank
ST-0
6—
——
——
——
—
Brennan and others—Fecal Indicator B
acteria and Gene M
arkers of Pathogenic Bacteria in G
reat Lakes Tributaries, March–O
ctober 2011—Open File Report 2015–1013
ISSN 2331-1258 (online)http://dx.doi.org/10.3133/ofr20151013