U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2012–5087

Prepared in cooperation with the West Virginia Department of Agriculture

Interlaboratory Comparison of Results for Three Microbial 

Source Tracking Quantitative Polymerase Chain Reaction 

(qPCR) Assays from Fecal-Source and Environmental Samples
Cover photo courtesy of West Virginia Department of Agriculture.
Interlaboratory Comparison of Results 

for Three Microbial Source Tracking 

Quantitative Polymerase Chain Reaction 

(qPCR) Assays from Fecal-Source and 

Environmental Samples

By Erin A. Stelzer, Kriston M. Strickler, and William B. Schill

Prepared in cooperation with the West Virginia Department of Agriculture

Scientific Investigations Report 2012–5087

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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Suggested citation:

Stelzer, E.A., Strickler, K.M., and Schill, W.B., 2012, Interlaboratory comparison of three microbial source tracking 

quantitative polymerase chain reaction (qPCR) assays from fecal-source and environmental samples: U.S. Geological 

Survey Scientific Investigations Report 2012–5087, 10 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Methods of Study...........................................................................................................................................2

Analytical Laboratories........................................................................................................................2

Sample Collection.................................................................................................................................2

Filtration and DNA Extraction .............................................................................................................2

Interlaboratory Differences ................................................................................................................2

qPCR Analyses ......................................................................................................................................2

Standard Curves and DNA Standards...............................................................................................3

Quality Assurance/Quality Control.....................................................................................................4

Data Analysis.........................................................................................................................................4

Interlaboratory Comparison of Standard Curves .....................................................................................5

Interlaboratory Comparison of Results from Microbial Source Tracking Assays ..............................5

Summary and Conclusion.............................................................................................................................9

References Cited..........................................................................................................................................10

Tables

1. Equipment and analytical differences among laboratories ..................................................3

2. Performance characteristics of quantitative polymerase chain reaction (qPCR) 

standard curves for each laboratory and microbial source tracking (MST) assay ..........5

3. Sample concentrations for all three microbial-source tracking (MST) assays 

from each laboratory....................................................................................................................7

4. Geometric means of absolute relative precent differences (ARPDs) for all samples 

and laboratories for each microbial source tracking (MST) assay before and 

after applying adjustment factors to sample concentrations for laboratory 3...................8

5. Friedman’s and Tukey’s studentized range multiple comparison statistical 

results for each microbial source tracking (MST) assay before and after 

applying adjustment factors to sample concentrations for laboratory 3 ............................8

6. Geometric means of absolute relative percent differences (ARPDs) for all 

samples for individual laboratories for each microbial source tracking (MST) 

assay before and after applying adjustment factors to sample concentrations 

for laboratory 3 .............................................................................................................................9
iv

Conversion Factors and Abbreviations

Inch/Pound to SI

Multiply By To obtain

Length

meter (m) 3.281 foot (ft)

millimeter (mm) 0.03937008 inch (in)

micrometer (μm) 0.00003937 foot (ft)

Volume

liter (L) 33.8140227 ounce, fluid (fl. oz)

milliliter (mL) 0.03381 ounce, fluid (fl. oz)

microliter (μL) 0.00003381 ounce, fluid (fl. oz) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Abbreviations

ANOVA analysis of variance

ARPD absolute relative percent difference

BSA Bovine serum albumen

Ct cycle threshold

CTAB hexadecyltrimethylammonium bromide

DNA deoxyribonucleic acid

E. coli Escherichia coli

MST microbial source tracking

NTC sno-template controls

qPCR quantitative polymerase chain reaction

USGS U.S. Geological Survey

WVDA West Virginia Department of Agriculture
Interlaboratory Comparison of Results for Three 

Microbial Source Tracking Quantitative Polymerase 

Chain Reaction (qPCR) Assays from Fecal-Source and 

Environmental Samples

By Erin A. Stelzer1, Kriston M. Strickler2, and William B. Schill3

Abstract

During summer and early fall 2010, 15 river samples and 

6 fecal-source samples were collected in West Virginia. These 

samples were analyzed by three laboratories for three microbial source tracking (MST) markers: AllBac, a general fecal 

indicator; BacHum, a human-associated fecal indicator; and 

BoBac, a ruminant-associated fecal indicator. MST markers 

were analyzed by means of the quantitative polymerase chain 

reaction (qPCR) method. The aim was to assess interlaboratory precision when the three laboratories used the same MST 

marker and shared deoxyribonucleic acid (DNA) extracts of 

the samples, but different equipment, reagents, and analyst 

experience levels. The term assay refers to both the markers 

and the procedure differences listed above. Interlaboratory 

precision was best for all three MST assays when using the 

geometric mean absolute relative percent difference (ARPD) 

and Friedman’s statistical test as a measure of interlaboratory 

precision. Adjustment factors (one for each MST assay) were 

calculated using results from fecal-source samples analyzed 

by all three laboratories and applied retrospectively to sample 

concentrations to account for differences in qPCR results 

among labs using different standards and procedures. Following the application of adjustment factors to qPCR results, 

ARPDs were lower; however, statistically significant differences between labs were still observed for the BacHum and 

BoBac assays. This was a small study and two of the MST 

assays had 52 percent of samples with concentrations at or 

below the limit of accurate quantification; hence, more testing 

could be done to determine if the adjustment factors would 

work better if the majority of sample concentrations were 

above the quantification limit.

1

U.S. Geological Survey, Ohio Water Science Center, Columbus, Ohio.

2

West Virginia Department of Agriculture, Regulatory and Environmental 

Affairs, Moorefield, West Virginia.

3

U.S. Geological Survey, Leetown Science Center, Leetown, West Virginia.

Introduction

Microbial source tracking (MST) tools are currently 

(2012) being used as a means to differentiate fecal contamination sources (U.S. Environmental Protection Agency, 2005). 

MST tools are divided according to two basic approaches: 

library-dependent methods, which rely upon large collections 

of known-source fecal-indicator bacteria; and library-independent methods, which utilize host-associated genetic markers. 

The library-dependent methods are applicable to an unlimited 

range of hosts, but are prone to false-positive results (Griffith 

and others, 2003; Stoeckel and others, 2004). Library-independent methods are limited in the range of hosts, but are less 

prone to false-positive results than library-dependent methods 

(Griffith and others, 2003).

A commonly used group of library-independent MST 

markers relies on the detection of 16S rRNA-based genetic 

markers from the fecal anaerobes of the order Bacteroidales. 

These obligate anaerobes make up about one-third of the 

human fecal flora, far outnumbering coliforms (Holdeman and 

others, 1976; Salyers, 1984). Bacteroidales’ host-associated 

markers have been used in several studies to detect human 

and ruminant fecal contamination (Boehm and others, 2003; 

Bower and others, 2005; Shanks and others, 2006; Seurinck 

and others, 2005; Kildare and others, 2007). 

An emerging library-independent MST method is quantitative polymerase chain reaction (qPCR). This technique 

cannot only be used to detect, but also to estimate the amount 

of MST marker present in samples. Many systems capable of 

running qPCR are now commercially available, and there is 

concern about assuming comparability of results generated by 

different laboratories using protocols without common equipment, reagents, and standards.

The U.S. Geological Survey (USGS), in cooperation with 

West Virginia Department of Agriculture (WVDA), assessed 

interlaboratory precision in MST assay concentrations when 

the same MST markers were applied to shared samples; 

however, there were differences in the equipment, reagents, 
2 Interlaboratory Comparison of Results for Three Microbial Source Tracking Quantitative Polymerase Chain Reaction Assays

and standards between the analytical laboratories. Due to the 

lack of standardized protocols and quality control, results 

from different laboratories may vary and at this time there 

is little guidance on how to determine the true MST marker 

concentration by qPCR. Twenty-one samples were analyzed 

by three laboratories using three MST assays. All analyses by 

the different laboratories were performed on deoxyribonucleic 

acid (DNA) extracts from the same set of samples to eliminate variability associated with samples, sample handling, 

and DNA extraction. Each laboratory/analyst had a different 

level of qPCR experience: one was a novice, another had 

approximately 5 years of experience, and another had more 

than 10 years of experience. Understanding the interlaboratory 

precision when using different equipment, reagents, and experience levels would help MST researchers to compare data 

from multiple laboratories within one study or even compare 

similar MST data among multiple studies, which can be rather 

complicated.

Methods of Study

Analytical Laboratories

Three laboratories participated in this study: a West 

Virginia state laboratory and two Federal laboratories. A single 

analyst at each of the laboratories handled all of their laboratories’ analytical work for this study.

Sample Collection

During September 2010, personnel from WVDA and 

the USGS in Charleston, West Virginia, collected seven river 

samples and six fecal-source samples in south-eastern West 

Virginia. All river samples were collected approximately 0.3 m 

below the water surface into sterile bottles using a grab-sampling technique (Myers and others, 2007). Fecal-source samples from chickens, cows, influent, and two effluent samples 

from a wastewater-treatment plant and a discharge pipe into a 

river were collected using sterile bottles or bags. Fecal-source 

samples were taken from farms or wastewater-treatment plants 

in the area, and chicken and cow feces were composited by 

species. Influent was collected by grab-sampling from the settling pond, and effluent was collected by grab-sampling from 

the wastewater-treatment plant.

The USGS in Leetown, West Virginia, provided eight 

additional river samples that were collected as part of another 

study during summer 2010. These samples were from sites in 

the Shenandoah Valley and were selected to be representative 

of surface-water samples that were thought to contain fecal 

contaminants from cattle, chicken, and human sources. These 

samples were collected in sterile bottles (as previously mentioned) and kept frozen until they were filtered and extracted.

Filtration and DNA Extraction

River and fecal-source samples collected in September 

2010 were filtered and extracted by WVDA within 48 hours 

of collection. The chicken and cow source samples were made 

into slurries by adding 1 g of feces to 99 mL of sterile-phosphate buffer. All samples were concentrated by use of 47-mm 

diameter, 0.4-μm pore size polycarbonate filters (Whatman, 

Florham Park, New Jersey). After filtration, each filter was 

aseptically folded and placed into a 2.0-mL screw-cap tube 

containing 0.3 g of acid-washed glass beads (Sigma, St. Louis, 

Missouri). Samples were extracted using a DNA-EZ extraction 

kit (GeneRite, North Brunswick, N.J.) according to manufacturer’s instructions. The final extract volume for each sample 

was 200 μL, which was split into three tubes. One tube was 

kept by the laboratory that filtered and extracted and the other 

two tubes were shipped on dry ice to the other laboratories. 

All DNA extracts were stored at −20 or −70°C until qPCR 

analysis.

Samples of river water (1 L) provided by USGS in 

Leetown, were filtered and extracted using a hexadecyltrimethylammonium bromide (CTAB) method (Karl and Bailiff, 

1989; Ishii and others, 1998). Crude DNA was further purified 

using a Clean and ConcentratorTM – 5 Kit (Zymo Research, 

Irvine, California). Purified DNA was eluted in 500 μL of 

IDTE, pH 8.0 (Integrated DNA Technologies, Inc., Coralville, 

Iowa) and stored frozen at −70°C until distribution to the other 

laboratories.

Interlaboratory Differences

The aim of this study was to do an interlaboratory comparison of results from MST assays. Sample processing up to 

qPCR was constant since samples were filtered and extracted 

by one laboratory and then distributed to the other laboratories. All laboratories had different analysts and used different 

qPCR systems and reagents. One laboratory used different 

qPCR reaction volumes and different DNA standard material; 

however, with accurate quantification these differences should 

not affect precision. Table 1 contains the differences that could 

influence the interlaboratory precision in this study.

qPCR Analyses

In all three laboratories, DNA extracts were analyzed for 

the same three MST markers using primer and probe sets as 

well as run conditions from previously published protocols: 

in each sample the AllBac marker (Layton and others, 2006) 

was used to estimate total Bacteroidales, the BacHum marker 

(Kildare and others, 2007) was used to measure human-associated Bacteroidales, and the BoBac marker (Layton and others, 

2006) was used to measure ruminant-associated Bacteroidales. 

The term MST assay, when used in this report, refers to both 
Methods of Study 3

the standardized marker listed above and the differences in 

protocol from each laboratory (table 1). In laboratory 1, all 

qPCR analyses were done using 5 μL of DNA extract and 

20 μL of master mix containing Quantitect Probe PCR kit 

(Qiagen, Valencia, Calif.) and Bovine serum albumen (BSA) 

(Invitrogen, Carlsbad, Calif.) in Smartcycler or Smartcycler II 

(Cepheid, Sunnyvale, Calif.) thermocyclers. In laboratory 2, 

all qPCR analyses were done using 5 μL of DNA extract and 

20 μL of master mix containing 2x Universal TaqMan Master 

Mix (Applied Biosystems, Foster City, Calif.) and BSA (Invitrogen, Carlsbad, Calif.) in a 7500 Real-Time PCR System 

(Applied Biosystems, Foster City, Calif.) thermocycler. In 

laboratory 3, all qPCR analyses were done using 2 μL of DNA 

extract and 10 μL of master mix containing QuantiFast Multiplex PCR + R kit (Qiagen, Valencia, Calif.) and BSA (Sigma, 

St. Louis, Mo.) in a Corbett Rotor-Gene 3000 (Qiagen, Valencia, Calif.) thermocycler. See table 1 for all the differences that 

could influence the interlaboratory precision in this study.

After completion of the qPCR analyses, some qPCR systems offer the ability for the researcher to manually designate 

a cycle threshold (Ct) value to determine at what point in the 

exponential phase the samples will be measured and the start 

of the baseline (the initial cycles of PCR during which there 

is little change in fluorescence signal) (Kephart and Bushon, 

2009). All three laboratories used an automatic baseline determined by the individual system and, if allowed, manually set 

the threshold at a value they determined to be the best fit in 

the exponential phase, which then was used for all qPCR runs 

of the same assay in that laboratory. Sample concentrations 

were calculated as assay copy number per 100 mL using the 

standard curves from each laboratory:

Conc = (sample Ct – y-intercept)/slope x

(extraction elution volume/volume added to 

qPCR reaction) x (100 mL/volume filtered).

Standard Curves and DNA Standards

A standard curve is generated by plotting cycle threshold 

values against known quantities of DNA from serially-diluted 

standards. Results from this set of standard reactions then are 

used to determine a best-fit regression line. DNA concentrations of environmental and fecal-source samples are calculated 

using this standard curve regression line (Applied Biosystems, 

2010).

Laboratories 1 and 2 used plasmid DNA standards created at laboratory 2 to develop their standard curves. A plasmid is a DNA molecule contained in some type of bacteria that 

is separate from, and can replicate independently of, chromosomal DNA. Plasmids promote gene transfer, and therefore, 

easily incorporate and retain non-native genes. A positive 

control for each MST assay was amplified by PCR and cloned 

into a PCR-TOPO plasmid (Invitrogen, Carlsbad, Calif.). 

The plasmid was transformed into Escherichia coli (E. coli)

TOP10 cells, and recombinant bacteria were selected on 

Table 1. Equipment and analytical differences among laboratories.

[qPCR, quantitative polymerase chain reaction; DNA, deoxyribonucleic acid]

Category Differences by laboratory

Laboratory 1 Laboratory 2 Laboratory 3

Thermocycler Cephied

Smartcycler and 

Smartcycler II

Applied Biosystems

7500 Real-Time

 PCR System

Corbett 

Rotor-Gene

3000

qPCR reagents Quantitect Probe

PCR kit

2x Universal 

TaqMan Master

Mix

QuantiFast

Multiplex PCR + R kit

qPCR reaction volumes 5 microliters 5 microliters 2 microliters

DNA standards Plasmids created by 

laboratory 2

Plasmids created by 

laboratory 2

Commercially 

synthesized 

standards

Analyst experience

 levels

Novice 5 years 10+ years

(1)
4 Interlaboratory Comparison of Results for Three Microbial Source Tracking Quantitative Polymerase Chain Reaction Assays

ampicillin-containing LB agar. Real-time TaqMan PCR was 

used to screen colonies for presence of the target insert, and 

isolated colonies were selected for overnight liquid-culture 

propagation. Plasmids were extracted from the transformed E. 

coli using UltraClean 6 Minute Mini Plasmid Prep kit (MoBio, 

Carlsbad, Calif.), and inserts were sequenced to confirm identity. Plasmids were quantified using the PicoGreenTM assay 

(Molecular Probes, Inc., Eugene, Oregon) and were serially 

diluted (10-fold dilutions) to generate standard curves. 

Laboratory 3 purchased synthesized standards for each 

MST assay from Integrated DNA Technologies (Coralville, 

Ia.). Synthesized standards are commercially produced by 

artificially adhering a prescribed sequence of bases together 

to produce the target gene sequence. After quantification by 

laboratory 3, these synthesized standards were serially diluted 

100-fold to generate standard curves. A single standard curve 

was analyzed with each batch of test samples in all three 

laboratories.

Quality Assurance/Quality Control

Quality-control samples for qPCR included no-template 

controls (NTCs) and qPCR positive controls. The NTCs were 

processed once per qPCR batch by using sterile moleculargrade water in place of DNA template. A standard curve was 

added to every qPCR batch as a qPCR positive control.

Matrix inhibition of the environmental and fecal-source 

samples was measured by use of the SPUD assay by laboratory 1 before laboratories 2 and 3 analyzed the samples (Nolan 

and others, 2006). Ct values for all samples were within two 

cycles of the expected value for the positive control, and thus, 

were not considered to be matrix inhibited.

Data Analysis

Precision refers to the ability of a measurement to be 

consistently reproduced. If a sample of water is analyzed two 

times, measurements that are close together in magnitude 

are said to have “good precision” (Kinzelman and others, 

2011). The measurement of precision used in this report is the 

absolute relative percent difference (ARPD), determined as 

follows: 

ARPD = ABS(X1-X2)/Xavg x 100 (2)

where 

X1 is concentration observed with the first replicate, 

X2 is concentration observed with the second replicate, 

and 

Xavg is average concentration = ((X1 + X2) / 2). 

When interpreting these results, the lower the relative 

percent difference, the greater the precision. The ARPD values 

were calculated using copy number per 100 mL. Geometric 

means of ARPDs for a given assay were calculated to facilitate 

a qualitative comparison across laboratories.

Three different statistical tests were performed in order to 

have a more quantitative comparison of laboratories. Friedman’s test (Friedman, 1940) was used to test the null hypothesis that the median concentrations from the laboratories for a 

given assay were equal, versus the alternative hypothesis that 

at least one of the medians is different. Concentrations from a 

given assay were ranked within blocks corresponding to the 21 

unique samples, and each laboratory was considered a separate 

treatment within the block. An analysis of variance (ANOVA) 

test was run on the ranked laboratory data along with posthoc 

Tukey’s Studentized Range multiple comparison tests (when 

ANOVA indicated significant differences) to facilitate pair 

wise comparisons of median concentrations among laboratories. All tests of significance were based on an alpha level of 

0.05.

It is common practice for researchers to use standardized 

controls that are analyzed by all laboratories participating in 

an interlaboratory comparison of methods (Vermeulen and 

others, 2009). Although not ideal, this practice may enable 

adjustment factors to be calculated and retrospectively applied 

to a laboratory’s results if they significantly differ from the 

results of another laboratory. In this study, the fecal-source 

samples were used as standardized controls. Ratio adjustment 

factors were computed for laboratory 3 for each MST assay. 

The adjustment factors (F) were computed (equation 3) and 

multiplied by the original results from laboratory 3 to account 

for its differences in method and controls.

(3)

where 

X1i is concentration for fecal source i by laboratory 1, 

X2i is concentration for fecal source i by laboratory 2, 

X3i is concentration for fecal source i by laboratory 3, 

and n and m are the numbers of fecal-source samples analyzed 

by laboratories 1 and 2, respectively.

1 1 1 2

3 3

i j

j i

n m i j

X X

X X

F

m n

= =

+

= +

∑ ∑
Interlaboratory Comparison of Results from Microbial Source Tracking Assays 5

Interlaboratory Comparison of 

Standard Curves

Standard-curve performance characteristics data from 

all three laboratories are provided in table 2. Guidelines for 

interpreting standard-curve data are available in the Applied 

Biosystems StepOne and StepOnePlus Real-Time PCR 

Systems Reagent Guide (Applied Biosystems, 2010). The 

amplification efficiency of the qPCR should be 90–110 percent; an efficiency of 100 percent means an exact doubling of 

the target DNA sequence at each cycle. This corresponds to a 

slope of about −3.1 to −3.6. In this study, the range of amplification efficiencies for all laboratories and all MST assays 

was 89 to 116 percent. Slopes ranged from −2.992 to −3.630. 

The dynamic range describes the lowest and highest standards 

analyzed by each laboratory in copies per qPCR reaction. 

Laboratories 1 and 2 have similar dynamic ranges since they 

shared the same lot of plasmid standards. The y-intercept is 

the Ct value where the standard curve crosses the y-axis at 

1 copy of the target sequence DNA. The y-intercepts in this 

study ranged from 34.58 to 44.74. The correlation coefficient 

(R2) is used to assess the fit of the standard curve to the plotted 

data points. The closer the R2 value is to 1, the better the fit. In 

this study, the R2 values ranged from 0.976 to 1.000.

Interlaboratory Comparison of Results 

from Microbial Source Tracking 

Assays

Replicates of the 21 DNA extracts for the same three 

MST qPCR targets were analyzed by three laboratories. DNA 

concentrations for each sample, by laboratory and assay, are 

provided in table 3. One or more of the differences in protocol 

from the three laboratories likely caused laboratory 3 to report 

much higher sample concentrations than did laboratories 1 

and 2. In order to bring sample concentrations for laboratory 3 

more in line with sample concentrations of laboratories 1 and 

2, adjustment factors were calculated and applied as described 

in the Data Analysis section of this report. The mean adjustment factors for AllBac, BacHum and BoBac were determined 

to be 0.42, 0.38, and 0.54, respectively. The adjustment factors 

and original and adjusted sample concentrations for laboratory 

3 are provided in table 3. 

Table 2. Performance characteristics of quantitative polymerase chain reaction (qPCR) standard curves for each 

laboratory and microbial source tracking (MST) assay. 

[R2, correlation coefficient; AllBac, general fecal indicator; BacHum, human-associated fecal indicator; BoBac, ruminant-associated fecal 

indicator]

Assay Laboratory Slope y-intercept R2 Dynamic range

(copies/qPCR reaction)

Amplification 

efficiency

(in percent)

AllBac 1 -3.630 42.85 0.991 46.6 - 4.66E+07 89

AllBac 2 -3.584 38.44 0.999 46.6 - 4.66E+07 90

AllBac 3 -2.992 34.58 0.996 120 - 1.20E+10 116

BacHum 1 -3.477 39.93 0.999 45.1 - 4.51E+07 94

BacHum 2 -3.527 38.72 0.999 22.3 - 2.23E+06 92

BacHum 3 -3.230 43.59 0.999 120 - 1.20E+10 104

BoBac 1 -3.336 44.74 0.976 46.3 - 4.63E+07 99

BoBac 2 -3.540 42.59 1.000 36.2 - 3.62E+06 92

BoBac 3 -3.315 38.01 0.999 120 - 1.20E+10 100
6 Interlaboratory Comparison of Results for Three Microbial Source Tracking Quantitative Polymerase Chain Reaction Assays

Table 3. Sample concentrations for all three microbial-source tracking (MST) assays from each laboratory.

[mL, milliliter; AllBac, general fecal indicator; BacHum, human-associated fecal indicator; BoBac, ruminant-associated fecal indicator; <, less than; --, 

sample not analyzed; bold values indicate concentration is at or below the limit for acurate quantification]

Sample

 name

Volume 

filtered

(mL)

Extraction 

elution 

volume

(mL)

AllBac

copies/

100 mL

Laboratory

1

Laboratory

2

Laboratory

3

Laboratory 

3

adjusted

Computed

adjustment

factors

River 1 450 0.2 44 45 120 50 

River 2 500 0.2 42 40 99 41 

River 3 100 0.2 180 190 480 200 

River 4 100 0.2 200 210 480 200 

River 5 100 0.2 190 180 470 196 

River 6 100 0.2 200 190 390 162 

River 7 100 0.2 190 190 410 171 

River 8 1,000 0.5 48 49 120 50 

River 9 1,000 0.5 54 54 130 54 

River 10 1,000 0.5 33 32 70 29 

River 11 1,000 0.5 57 56 140 58 

River 12 1,000 0.5 55 53 130 54 

River 13 1,000 0.5 44 43 98 41 

River 14 1,000 0.5 53 51 120 50 

River 15 1,000 0.5 60 59 140 58 

Source 1 150 0.2 127 120 320 133 0.39 

Source 2 10 0.2 3,000 3,000 7,200 2,996 0.42 

Source 3 50 0.2 620 620 1,500 624 0.41 

Source 4 20 0.2 1,300 1,200 2,900 1,207 0.43 

Source 5 100 0.2 170 170 450 187 0.38 

Source 6 100 0.2 170 170 360 150 0.47 
Interlaboratory Comparison of Results from Microbial Source Tracking Assays 7

Table 3. Sample concentrations for all three microbial-source tracking (MST) assays from each laboratory.—Continued

[mL, milliliter; AllBac, general fecal indicator; BacHum, human-associated fecal indicator; BoBac, ruminant-associated fecal indicator; <, less than; --, sample 

not analyzed; bold values indicate concentration is at or below the limit for acurate quantification]

BacHum

copies/100 mL

BoBac

copies/100 mL

Laboratory

1

Laboratory

2

Laboratory

3

Laboratory 

3

adjusted

Computed

adjustment

factors

Laboratory

1

Laboratory

2

Laboratory

3

Laboratory 

3

adjusted

Computed 

adjustment

factors

9 10 25 10 17 21 43 23

22 24 52 20 20 22 36 19

34 14 110 42 120 140 270 146

79 68 150 58 110 110 220 119

78 14 110 42 93 120 230 124

100 120 250 96 74 87 110 59

110 120 240 92 67 93 140 76

10 9 15 6 27 33 57 31

36 39 88 34 35 38 69 37

10 4 18 7 16 26 43 23

25 28 59 23 45 50 110 59

<1 12 13 5 44 47 100 54

12 17 41 16 31 36 68 37

10 6 16 6 43 46 96 52

24 27 61 23 51 56 120 65

44 35 74 29 0.53 39 45 78 42 0.54

8 140 480 185 0.15 2,700 -- 6,400 3,454 0.42

490 530 1,200 462 0.43 480 490 930 502 0.52

1,000 1,000 2,400 925 0.42 810 780 1,100 594 0.72

33 39 110 42 0.33 57 39 64 35 0.75

100 100 220 85 0.45 70 74 320 173 0.23
8 Interlaboratory Comparison of Results for Three Microbial Source Tracking Quantitative Polymerase Chain Reaction Assays

Prior to adjustments, the geometric means of ARPDs for 

all three laboratories, by MST assay, were 23.1, 48.9, and 35.2 

for AllBac, BacHum, and BoBac, respectively (table 4). Friedman’s test indicated that at least one of the unadjusted laboratory concentrations was statistically different from the others 

for all three assays (table 5). The geometric means of ARPDs 

were substantially lower at 2.9, 19.4, and 11.2 for AllBac, 

BacHum, and BoBac, respectively (table 4), after adjustment 

of results for laboratory 3. Friedman’s test on the adjusted concentrations did not indicate statistically significant differences 

among laboratories for the AllBac assay results; however, 

statistically significant differences still were indicated for both 

the BacHum and BoBac assays (table 5).

The differences in protocol used in laboratory 3 may have 

resulted in low precision of sample concentrations compared 

to laboratories 1 and 2. Adjustment factors applied to sample 

concentrations for laboratory 3 helped to heighten the precision across all three MST assays; however, BacHum and 

BoBac still showed statistically significant differences among 

the three laboratories. One possible reason why BacHum 

and BoBac still showed statistically significant differences 

Assay n

Geometric mean

ARPD

Unadjusted Adjusted

AllBac 21 23.1 2.9

BacHum 21 48.9 19.4

BoBac 20 35.2 11.2

Table 4. Geometric means of absolute relative precent 

differences (ARPDs) for all samples and laboratories for each 

microbial source tracking (MST) assay before and after applying 

adjustment factors to sample concentrations for laboratory 3. 

[n, number of values included in the ARPD calculation; AllBac, general fecal 

indicator; BacHum, human-associated fecal indicator; BoBac, ruminantassociated fecal indicator]

Assay Laboratory Friedman test

p value

Tukey studentized

 range grouping

Unadjusted

AllBac 1

<0.0001

ND

2

3

BacHum 1

2 <0.0001

3

BoBac 1

2 <0.0001

3

Adjusted

AllBac 1

2 0.3041 ND

3

BacHum 1

0.0309

A B

2 A

3 B

BoBac 1

0.0012

A

2 A B

3 B

Table 5. Friedman’s and Tukey’s studentized range multiple comparison statistical results for 

each microbial source tracking (MST) assay before and after applying adjustment factors to 

sample concentrations for laboratory 3.

[AllBac, general fecal indicator; <, less than; ND, not done; BacHum, human-associated fecal indicator; BoBac, 

ruminant-associated fecal indicator; a p value ≤ 0.05 is considered statistically significantly different; Tukey 

studentized range grouping are presented as letters, and laboratories with at least one letter in common do not 

difffer significantly]
Summary and Conclusion 9

could be that 52 percent of the concentrations for these two 

assays were at or below the limit of accurate quantification 

and very near or at the detection limit of the assays, making 

them slightly more uncertain than concentrations for AllBac, 

which were almost all above the limit of quantification and 

well above the detection limit. All concentrations at or below 

the limit of accurate quantification are indicated in bold type 

in table 3.

In the interlaboratory comparison, laboratories 1 and 2 

had the lowest geometric means of ARPDs for all three MST 

assays when using the unadjusted concentrations (table 6). 

After adjustments, the geometric means of ARPDs were lowest for laboratories 1 and 2 for AllBac (1.9), for laboratories 

1 and 3 for BacHum (19.0), and for laboratories 2 and 3 for 

BoBac (8.0) (table 6). These results could be an artifact of 

how the adjustment factors were computed; therefore, more 

statistical tests were run. Tukey’s Studentized Range test was 

run as a posthoc test if the ANOVA test indicated a significant 

difference. Tukey’s Studentized Range test ranked laboratories against each other in terms of statistical similarities based 

on their sample concentrations. These tests were run only on 

adjusted concentrations from laboratory 3 to further explore 

the nature of the differences indicated in Friedman’s tests 

using the adjusted concentrations for laboratory 3. Differences 

among laboratory results for AllBac were not statistically 

significant. Results for BacHum indicated that laboratories 2 

and 3 had statistically significant differences, whereas results 

for BoBac indicated that laboratories 1 and 3 had statistically 

significant differences (table 5).

In both cases of statistically significant differences after 

adjustment (BoBac and BacHum assays), laboratory 3 was 

one of the laboratories singled out. This may be because many 

of the sample concentrations for these two assays were below 

the lowest point on the standard curve, and therefore, not as 

accurately calculated. 

Summary and Conclusion

Microbial source tracking (MST) tools are commonly 

being used to help differentiate sources of fecal contamination in environmental waters. Currently (2012), there is a 

wide array of commercially available quantitative polymerase 

chain reaction (qPCR) systems and reagents, which has led to 

a concern about comparability of data generated by different 

laboratories using these different equipment and reagents. The 

U.S. Geological Survey, in cooperation with the West Virginia 

Department of Agriculture, assessed interlaboratory variability 

in MST assay concentrations when using the same MST markers and shared samples. Three laboratories shared deoxyribonucleic acid (DNA) extracts from 15 river and 6 fecal-source 

samples and ran each sample with three MST assays to 

determine if qPCR concentrations are interchangeable among 

laboratories. Each laboratory used different qPCR systems and 

reagents and one laboratory used different standards and qPCR 

reaction volumes. Results indicated that geometric mean 

ARPDs showing qPCR precision for laboratory 3 were all at 

or above 58.3, whereas the geometric mean ARPDs for just 

laboratories 1 and 2 were all at or below 19.2. Although not 

ideal, through the use of control samples that were analyzed 

by all participating laboratories, adjustment factors were 

applied to sample results for laboratory 3, which brought the 

geometric mean ARPDs down to at or below 20.1. Technically, the use of different standards (if accurately quantified) 

and different qPCR reaction volumes should not have caused 

the large precision issue that was discovered in this study. As 

previously stated in this report, the use of the adjustment factors was not ideal, but needed in order to compare data from 

all the laboratories for this report. Therefore, additional study 

is needed to test interlaboratory variability with only one variable changing at a time and with all samples above the assay 

limit of quantification. 

Table 6. Geometric means of absolute relative percent differences (ARPDs) for all samples for individual 

laboratories for each microbial source tracking (MST) assay before and after applying adjustment factors to sample 

concentrations for laboratory 3.

[n, number of values included in the ARPD calculation; AllBac, general fecal indicator; BacHum, human-associated fecal indicator; 

BoBac, ruminant-associated fecal indicator]

Assay Laboratories 1 and 2 Laboratories 1 and 3 Laboratories 2 and 3

n

Geometric mean

ARPD n

Geometric mean

ARPD n

Geometric mean

ARPD

Unadjusted

AllBac 21 1.9 21 80.3 21 81.0

BacHum 21 19.2 21 78.5 21 77.7

BoBac 20 11.5 21 65.8 20 58.3

Adjusted

AllBac 21 1.9 21 4.7 21 2.4

BacHum 21 19.2 21 19.0 21 20.1

BoBac 20 11.5 21 15.5 20 8.0
10 Interlaboratory Comparison of Results for Three Microbial Source Tracking Quantitative Polymerase Chain Reaction Assays

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Stelzer and others—Interlaboratory Comparison of Results for Three Microbial Source Tracking Quantitative Polymerase Chain Reaction Assays—SIR 2012-5087