U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2009–5097

In cooperation with the U.S. Environmental Protection Agency, 

National Homeland Security Research Center

Performance of Traditional and Molecular

Methods for Detecting Biological Agents in

Drinking Water
Cover image: View of ultrafiltration being done in a biosafety cabinet at the U.S. Geological Survey’s Ohio Water 

Microbiology Laboratory. (Photograph by Donna Francy, U.S. Geological Survey.)
Performance of Traditional and Molecular 

Methods for Detecting Biological Agents in 

Drinking Water

By Donna S. Francy, Rebecca N. Bushon, Amie M.G. Brady, Erin E. Bertke, 

Christopher M. Kephart, Christina A. Likirdopulos, Brian E. Mailot, 

Frank W. Schaefer, III, and H.D. Alan Lindquist

In cooperation with the U.S. Environmental Protection Agency, 

National Homeland Security Research Center

Scientific Investigations Report 2009–5097

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, ActingDirector

U.S. Geological Survey, Reston, Virginia: 2009

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Suggested citation:

Francy, D.S., Bushon, R.N., Brady, A.M.G., Bertke, E.E., Kephart, C.M., Likirdopulos, C.A., Mailot, B.E., Schaefer, F.W., 

III, and Lindquist, H.D.A. 2009, Performance of traditional and molecular methods for detecting biological agents in 

drinking water: U.S. Geological Survey Scientific Investigations Report 2009–5097, 17 p.
iii

Contents

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

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

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

Sampling Procedures...........................................................................................................................2

Ultrafiltration..........................................................................................................................................4

Microorganisms....................................................................................................................................4

Traditional Methods..............................................................................................................................5

Molecular Methods..............................................................................................................................6

Initial Processing and DNA Extraction ....................................................................................6

Quantitative PCR ..........................................................................................................................7

Data Analysis and Statistics ...............................................................................................................8

Analytical Results and Method Performance...........................................................................................8

Water Quality.........................................................................................................................................8

Standard Curves and Variability of Molecular Results...................................................................9

Microbial Recovery and Detection....................................................................................................9

Comparison of Number of Organisms Detected by Traditional and Molecular Methods .....11

Suggestions for Future Study ....................................................................................................................13

Summary and Conclusions.........................................................................................................................13

Acknowledgments.......................................................................................................................................15

References Cited .........................................................................................................................................15

Figures

1. Standard-curve plot of the cycle-threshold value versus log10-transformed 

concentrations of Burkholderia cepacia as determined by cultural methods...................9

 2. Graphs showing regression relations for quantiative polymerase chain reaction 

(qPCR) and culture or immunomagnetic separation/fluoresence antibody 

(IMS/FA) numbers for seeded retentate samples.................................................................12
iv

Tables

1. Site information and water-quality data for samples collected from Ohio 

drinking-water treatment plants ................................................................................................3

2. Primer and probe sequences for biological agents, final concentrations, 

and targets for each assay .........................................................................................................7

 3. Performance characteristics of quantitative polymerase chain reaction 

(qPCR) standard curves for each assay ..................................................................................9

4. Numbers of colony-forming units for bacteria or oocysts for C. parvum

used to seed 100-liter water samples as determined by culture or 

immunomagnetic separation/fluorescence antibody (IMS/FA) methods ...........................9

5. Recoveries by culture (for bacteria) or immunomagnetic separation/

fluoresence antibody (IMS/FA) (for C. parvum) methods and detections 

by quantiative polymerase chain reaction (qPCR) after ultrafiltration of 

pathogens seeded into 100-liter water samples ...................................................................10

6. Pearson’s r correlations between water quality and recoveries of biological 

agents ...........................................................................................................................................12

Conversion Factors

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch (in.)

micrometer (μm) 0.00003937 inch (in.)

Area

square meter (m2

) 10.76 square foot (ft2)

Volume

liter (L) 2.642 gallon (gal) 

milliliter (mL) 0.06102 cubic inch (in3

) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz) 

Acceleration

gravitational acceleration (g) 32.17 foot per second squared (ft/s2

)

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

°F=(1.8×°C)+32

Concentrations of total coliforms and Escherichia coli are given in colony-forming units per 

100 milliliters (CFU/100 mL).

In addition to milliliters, volumes are given in microliters (μL), which are 10-6 liter (10-3 milliliter).

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm 

at 25°C).

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).
Abstract

To reduce the impact from a possible bioterrorist attack 

on drinking-water supplies, analytical methods are needed 

to rapidly detect the presence of biological agents in water. 

To this end, 13 drinking-water samples were collected at 9 

water-treatment plants in Ohio to assess the performance of 

a molecular method in comparison to traditional analytical 

methods that take longer to perform. Two 100-liter samples 

were collected at each site during each sampling event; one 

was seeded in the laboratory with six biological agents—

Bacillus anthracis Sterne (B. anthracis), Burkholderia cepacia 

(as a surrogate for Bu. pseudomallei), Francisella tularensis 

Live Vaccine Strain (F. tularensis), Salmonella Typhi (S.

Typhi), Vibrio cholerae (V. cholerae), and Cryptospordium 

parvum (C. parvum). The seeded and unseeded samples were 

processed by ultrafiltration and analyzed by use of quantiative 

polymerase chain reaction (qPCR), a molecular method, and 

culture methods for bacterial agents or the immunomagnetic 

separation/fluorescent antibody (IMS/FA) method for C. parvum as traditional methods. Six replicate seeded samples were 

also processed and analyzed.

For traditional methods, recoveries were highly variable between samples and even between some replicate 

samples, ranging from below detection to greater than 100 

percent. Recoveries were significantly related to water pH, 

specific conductance, and dissolved organic carbon (DOC) 

for all bacteria combined by culture methods, but none of the 

water-quality characteristics tested were related to recoveries 

of C. parvum by IMS/FA. Recoveries were not determined by 

qPCR because of problems in quantifying organisms by qPCR 

in the composite seed. Instead, qPCR results were reported 

as detected, not detected (no qPCR signal), or +/- detected 

(Cycle Threshold or “Ct” values were greater than 40). Several sample results by qPCR were omitted from the dataset 

because of possible problems with qPCR reagents, primers, 

and probes. For the remaining 14 qPCR results (including 

some replicate samples), F. tularensis and V. cholerae were 

detected in all samples after ultrafiltration, B. anthracis was 

detected in 13 and +/- detected in 1 sample, and C. parvum

was detected in 9 and +/- detected in 4 samples. Bu. cepacia

was detected in nine samples, +/- detected in two samples, and 

not detected in three samples (for two out of three samples not 

detected, a different strain was used). The qPCR assay for V. 

cholerae provided two false positive—but late—signals in one 

unseeded sample. Numbers found by qPCR after ultrafiltration 

were significantly or nearly significantly related to those found 

by traditional methods for B. anthracis, F. tularensis, and 

V. cholerae but not for Bu. cepacia and C. parvum. A qPCR 

assay for S. Typhi was not available. 

The qPCR method can be used to rapidly detect B. 

anthracis, F. tularensis, and V. cholerae with some certainty in 

drinking-water samples, but additional work would be needed 

to optimize and test qPCR for Bu. cepacia and C. parvum and 

establish relations to traditional methods. The specificity for 

the V. cholerae assay needs to be further investigated. Evidence is provided that ultrafiltration and qPCR are promising 

methods to rapidly detect biological agents in the Nation’s 

drinking-water supplies and thus reduce the impact and consequences from intentional bioterrorist events. To our knowledge, this is the first study to compare the use of traditional 

and qPCR methods to detect biological agents in large-volume 

drinking-water samples. 

Introduction

Water supplies in the United States represent potential 

targets for terrorists wanting to disrupt society or damage 

important parts of the infrastructure (Meinhardt, 2005). In 

fact, there have been a number of incidents where disease 

agents have been spread unintentionally through drinkingwater systems, making intentional contaminantion of biological agents all the more likely (Lindquist and others, 2007). 

Even if such attacks on water systems do not result in massive 

casualties, they may result in societal disruptions (Gleick, 

2006). A priority concern for those involved with national 

security is protecting the critical infrastructure against the 

threat of bioterrorism through contaminated drinking water. It 

is recognized that early detection and rapid response are the 

Performance of Traditional and Molecular Methods for 

Detecting Biological Agents in Drinking Water

By Donna S. Francy, Rebecca N. Bushon, Amie M.G. Brady, Erin E. Bertke, Christopher M. Kephart, Christina 

A. Likirdopulos, Brian E. Mailot, Frank W. Schaefer, III, and H.D. Alan Lindquist
2 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

keys towards reducing the impact of a biological attack on a 

drinking-water supply (Meinhardt, 2005). To facilitate early 

detection, sampling techniques and analytical methods for 

large volumes of water are needed to quickly detect a variety 

of potential biological agents.

 Ultrafiltration (UF) is a method that can be used to concentrate multiple microorganisms simultaneously (MoralesMorales and others, 2003; Lim and others, 2005). Ultrafiltration uses size exclusion to concentrate microorganisms, 

where molecules smaller than the filter pore size pass through 

the membrane and to the effluent line while larger particles 

(such as microorganisms) are concentrated in the retentate 

and continue to recirculate within the filter apparatus. Large 

volumes of water can be filtered in this manner, keeping target 

organisms in suspension and reducing fouling of the membrane (Holowecky and others, 2009). Ultrafiltration has been 

shown to be effective in concentrating viruses, bacteria, and 

protozoan pathogens from large volumes of tap water (Hill 

and others, 2007; Polaczuk and others, 2008; Holowecky and 

others, 2009). 

After concentrating the target organisms by UF, analytical methods are needed to quickly detect their presence in 

the retentate. Traditional cultural and microscopic methods 

are considered the gold standard for isolation, detection, and 

identification of biological agents (Lim and others, 2005); 

however, these methods take days before any confirmatory 

answer is available. Molecular methods, such as quantitative 

polymerase chain reaction (qPCR), are sensitive and quantitative (Guy and others, 2003) and have the potential for rapid 

analysis of samples for biological agents from a suspected 

intentional release. Although it is understood that methods 

such as qPCR are more rapid and efficient than traditional 

methods, results from qPCR are still considered presumptive 

for biological agents. Sample testing must be done in conjunction with traditional cultural methods to provide confirmation 

of results. According to Roos and Egan (2008), no single 

method can confirm the presence of a biological threat; multiple tests are required. 

Quantitative PCR has been developed and tested for 

determining levels of protozoan pathogens (Guy 2003; Varma 

and others, 2003), bacterial indicators (Santo Domingo and 

others, 2003), and viruses (He and Jiang, 2005) in water matrices, but it has not been extensively tested on large-volume 

concentrates. In one study of 100-L water samples, investigators found that qPCR could effectively detect viral and bacterial indicators and Cryptosprodium parvum oocysts from UF 

concentrates but that water quality affected qPCR performance 

(Hill and others, 2007). Although rapid-detection technologies 

such as qPCR have been tested for biological agents (Polaczyk 

and others, 2008), few have been extensively evaluated under 

field conditions (Lim and others, 2005). More commonly, 

studies are done to test qPCR methods for biological agents in 

other settings, such as those for detection of Francisella tularensis in clinical samples (Fulop and others, 1996; Hepburn 

and others, 2006) or laboratory validation studies of isolates of 

Bacillus anthracis (Hoffmaster and others, 2002). Relatively 

little is known, however, about the ability of qPCR to detect 

biological agents in large-volume drinking-water samples and 

the performance of qPCR compared to traditional methods 

(Francy and others, in press). 

The U.S. Geological Survey (USGS), in collaboration 

with the U.S. Environmental Protection Agency (USEPA), 

National Homeland Security Research Center, collected 13 

raw and finished drinking-water samples to assess the utility and performance of qPCR in comparison to traditional 

analytical methods for detection of biological agents following UF. Although comparing recoveries of biological agents 

was an early objective of the study, problems in enumerating 

organisms in the composite seed precluded achieving this for 

qPCR; instead, we focused on the variability of recoveries by 

traditional methods and on detections of organisms by qPCR 

after UF. Other issues addressed during the study were identifying the best primary isolation medium for each biological 

agent, determining the effect of water quality on recoveries by 

traditional methods, and comparing the numbers of organisms 

detected by qPCR to those detected by traditional methods 

following UF. To investigate these issues, we targeted six 

waterborne biological agents: Bacillus anthracis, Burkholderia pseudomallei, Francisella tularensis, Salmonella Typhi, 

Vibrio cholerae, and Cryptospordium parvum. In addition to 

qPCR, samples were analyzed by use of traditional culture 

methods for bacterial agents and by immunomagnetic separation/immunofluorescence microscopy assay (IMS/FA) for C. 

parvum. This report is a companion report to Francy and others (in press) and presents method-performance information 

not included in the other report.

Methods of Study

Sampling Procedures

Raw and (or) finished drinking-water samples were collected from nine water-treatment plants in Ohio to include 

different types of source waters and water quality (table 1). 

Five sites were supplied by surface water, and four were 

supplied by ground water. Some sites were sampled multiple 

times, either to collect both raw and finished ground water 

or to confirm results. Finished drinking-water samples were 

collected from each water-treatment plant after treatment and 

immediately before distribution. All samples collected from 

surface-water sources were finished waters; treatment included 

coagulation, dual-media filtration, lime softening, and freechlorine disinfection. For finished ground-water samples, 

treatment included flocculation, lime softening, sand filtration, 

and free chlorine disinfection. Samples were collected from a 

laboratory or an outside spigot that was swabbed with ethanol, 

flame-sterilized, and rinsed with sterile deionized water before 

sampling. 
Methods of Study 3

Two 100-L subsamples were collected at each site during 

each sampling event. One was seeded in the laboratory with 

six target organisms, and the second was used to determine 

the natural incidence of target organisms and serve as negative 

controls (because it is unlikely that unseeded samples will be 

positive). Subsamples were collected into five 20-L cubitainer 

containers. For finished waters, each cubitainer contained 

sterile sodium thiosulfate solution to achieve a final concentration of 50 mg/L. The samples were stored in a field van when 

air temperatures were less than 21°C and drive time was less 

than 1 hour; otherwise, they were stored on ice for transport 

to the laboratory. In the laboratory, samples were stored at 

4°C and processed within 24 hours of collection. Because of 

the suspected loss of Burkholderia cepacia (a surrogate for 

Bu. pseudomallei) at cooler temperatures, samples collected 

later in the study were kept at room temperature overnight and 

allowed to reach 17 to 19°C before seeding and processing. 

Field quality-control samples for biological agents included 

an equipment blank (40 L of autoclaved tap water treated in 

the same manner as a regular sample) to assess contamination 

potential and replicate seeded samples at six sites to assess 

variability. 

Specific conductance, temperature, dissolved oxygen, 

and pH were measured onsite each time a sample was collected in accordance with standard USGS protocols (Wilde, 

2005). Alkalinity was measured using digital titration with 

sulfuric acid (Hach Model 16900, Hach Company, Loveland, 

Colo.)(Wilde, 2005, chap. 6.6). Turbidity was measured using 

a turbidimeter (Hach Model 2100P). Sterile tubing and 1-L 

sterile bottles containing sodium thiosulfate were used to 

collect samples for total coliforms and Escherichia coli (E. 

coli). Samples for total coliforms and E. coli were analyzed by 

means of the MI agar method (U.S. Environmental Protection 

Agency, 2002) within 6 hours of sample collection; they were 

included because they are standard drinking-water-sample 

analyses. Samples for dissolved organic carbon (DOC), calcium, and magnesium were shipped on ice by overnight mail 

to the USGS National Water-Quality Laboratory (NWQL) in 

Denver, Colo. DOC was analyzed by use of ultraviolet-promoted persulfate oxidation and infrared spectrometry (Brenton 

and Arnett, 1993). Calcium and magnesium concentrations 

were determined by use of atomic emission spectrometry and 

inductively coupled plasma (Fishman, 1993); these concentrations were used to calculate hardness (American Public Health 

Association and others, 1998, Section 2340 B). Quality-control samples for chemical constituents included a field blank 

(blank water treated in the same manner as a regular sample) 

and a replicate sample. Quality-control samples for total 

coliforms and E. coli included a replicate for every sample and 

two field blanks. For chemical constituents and bacterial indicators, concentrations in replicate samples were in the same 

range, and concentrations in blanks were below detection (data 

not shown but are available from the USGS Ohio Water Science Center in Columbus). 

Table 1. Site information and water-quality data for samples collected from Ohio drinking-water treatment plants.

[Modified from Francy and others (in press). R indicates replicates for two samples collected on the same date; I, II, and III indicate that samples were 

collected on three sampling dates. Abbreviations: SW is surface water (all SW samples were finished waters); GW is groundwater, μS/cm, microsiemens 

per centimeter at 25 degrees Celsius; NTU, nephelometric turbidity units; mg/L, milligrams per liter; CFU/100 mL, colony-forming units per 100 milliliters]

Site Date sampled Water sourcetreatment pH

Specific 

conductance 

(μS/cm)

Turbidity 

(NTU)

Alkalinity 

(mg/L as 

CaCO3

)

Hardness 

(mg/L as 

CaCO3)

Dissolved 

organic 

carbon 

(mg/L)

Total 

coliforms 

(CFU/100 

mL)a

1 20-Feb-07 SW 7.4 658 0.6 41 119 1.7 < 1

2 12-Mar-07 GW-raw, R 7.1 754 0.3 262 375 1.2 8, 7

2 05-Nov-07 GW-finished 7.6 598 0.2 29 122 0.9 < 1

3 09-Apr-07 SW I 9.5 249 0.1 44 81 1.2 < 1

3 10-Dec-07 SW II, R 9.4 257 0.3 44 91 1.8 < 1

3 11-Feb-08 SW III 9.7 413 0.4 82 109 2.2 < 1

4 07-May-07 GW-raw 7.4 614 0.2 201 276 0.9 < 1, 1

4 28-Jan-08 GW-finished, R 9.2 469 0.6 67 148 1.1 < 1

5 09-Jul-07 SW, R 8.1 258 0.2 29 90 2.3 < 1

6 30-Jul-07 GW-raw 6.4 435 0.5 132 188 0.3 < 1

7 20-Aug-07 SW 7.4 616 0.8 59 179 1.9 < 1

8 10-Sep-07 GW-finished, R 8.7 1,321 2.1 41 147 0.9 < 1

9 15-Oct-07 SW, R 8.7 802 0.3 26 238 1.7 < 1

a Each analysis was done in duplicate. Duplicate analyses that were not the same are reported.
4 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

Ultrafiltration

The 100-L water samples were processed in the laboratory by UF. The UF apparatus is described in detail in Hill and 

others (2007) and Lindquist and others (2007). The apparatus 

consisted of a peristaltic pump connected to an ultrafilter and 

polypropylene retentate bottle (used to contain the sample 

that was eluted from the filter) with sterilized silicon tubing, 

tubing connectors, and clamps. The hollow-fiber ultrafilters 

were single-use Minntech HHP Hemoconcentrators (Minntech 

Corp., Minneapolis, Minn.) or later in the study, Rexbrane 

Membrane High-Flux, REXEED-25S (Asahi Kasei Kuraray 

Medical Co., Ltd., Japan). The Minntech and Ashahi ultrafilters have molecular cutoffs of 65,000- and 29,000-Da, surface 

areas of 1.31 m2 and 2.5 m2, and fiber inner diameters of 200 

μm and 185 mm, respectively. Side-by-side qualitative comparisons indicated similar recoveries of biological agents by 

use of either filter (Holowecky and others, 2009). For seeded 

samples, the inoculum was injected into the sample line 

through an injection port by using a 60-mL syringe. 

Before filtering the sample, filter blocking was done by 

recirculating 1 L of 0.1 percent sodium polyphosphate through 

the UF apparatus. The blocking solution was reduced to 225 

mL in the retentate bottle, the intake tubing was placed into 

the first 20-L container of sample, and the retentate bottle was 

filled with sample water. For seeded samples, one-third of the 

composite seed was injected into the sample line during UF of 

the second, third, and fourth sample containers. When UF of 

the 100-L sample was complete (usually after 2−4 hours), the 

intake line was closed off and the retentate volume reduced 

to 225 mL. Forward and backflush rinses were done to elute 

target organisms from the ultrafilter. For the forward elution, 

400 mL of eluting solution (0.001 percent Tween 80) was 

pumped through the intake line. The 225-mL retentate from 

the forward rinse was poured into a 250-mL centrifuge tube, 

previously coated with 2.5 percent bovine serum albumin 

(BSA) (Sigma-Aldrich Co., St. Louis, Mo.). For the backflush 

elution, 300 mL of eluting solution was pumped through the 

effluent tubing, previously cut by using sterile technique. The 

225 mL backflush retentate was poured into a second 250-mL 

centrifuge tube. The forward and backflush retentate solutions were centrifuged at 3,300 g at 4°C for 30 min, and the 

pellets (15 mL) from both retentates were combined. The final 

retentate volume was determined for subsequent calculations. 

After processing each sample, UF equipment was autoclaved 

or disinfected with 10 percent sodium hypochlorite solution.

Microorganisms

Six microorganisms were composited and used to seed 

100-L water samples (“composite seed”). Bacillus anthracis

is the causative agent of anthrax, and although it is typically 

an airborne contaminant, B. anthracis is described as an 

agent of waterborne disease by Young (1975). For this study, 

the B. anthracis Sterne (“B. anthracis”) strain (Strain 34F2; 

Colorado Serum Co., Denver, Colo.), a veterinary vaccine 

for anthrax, was used. Burkholderia cepacia (ATCC 17616 

and 17759) was used as a surrogate for Bu. pseudomallei. Bu. 

pseudomallei causes meliodosis in humans, a potentially fatal 

infection endemic in northern Australia and Southeast Asia 

(Inglis and Sagripanti, 2006). Bu. cepacia is an opportunistic pathogen that is particularly dangerous in cystic fibrosis 

patients (Henry and others, 1997). Francisella tularensis is 

the causative agent of the zoonotic disease tularemia, found 

throughout the northern hemisphere and highly infectious by 

the aerosol route (Fulop and others, 1996). The F. tularensis

Live Vaccine Strain (“F. tularensis,” U.S. Centers for Disease Control and Prevention, Atlanta, Ga.) was used in this 

study. Salmonella enterica serovar Typhi (ATCC 19430) was 

formerly elevated to species level as S. typhi, but it is now 

recognized as a serovar and designated as S. Typhi. S. Typhi 

causes typhoid fever, a disease that is common in many parts 

of the developing world. V. cholerae 01 (ATCC 14035) causes 

the gastrointestinal disease cholera, and this particular strain 

was the causative agent of an epidemic in South America during the 1990s. Cryptosporidium parvum is the causative agent 

of cryptosporidiosis, a wide-spread gastrointenstinal disease 

that is especially dangerous for persons with compromised 

immune systems. Cryptosporidium parvum Harley Moon 

strain (Waterborne Inc., New Orleans, La.) was the only protozoan agent tested during this study. 

Fresh spore stocks of B. anthracis were prepared using 

a method that included New Sporulation Medium (NSM), 

modified from Purdue and others (2003) and described here. A 

frozen stock of B. anthracis was streaked onto three trypticase 

soy agar plus 5 percent sheep blood (TSA+SB) plates (Becton, 

Dickinson and Co., Sparks, Md.) and incubated overnight at 

35°C. Eight isolated colonies were suspended in phosphate 

buffered saline (PBS), and 200-μL aliquots were spread on 

each of five NSM plates. After 48 hours incubation at 35°C, 

a cell suspension was microscopically examined to ensure 

that at least 90 percent of cells were spores. Biomass from the 

NSM plates was scraped and washed with deionized water 

into two 33-mL centrifuge tubes. After two cycles of centrifugation at 12,300 g for 10 minutes at 25°C and subsequent 

washes with deionized water, the spore suspensions were 

composited and stored at 4°C for 24 hours to allow lysis of 

any vegetative cells. To enumerate spores, a 1-mL suspension 

was heat-treated for 60 minutes at 70°C and serially diluted to 

10-8, then 100 μL of appropriate dilutions were spread-plated 

onto TSA+SB plates. Colonies were counted after 24 hours 

incubation at 35°C. Aliquots of 1-mL spore stocks were then 

stored in deionized water at 4°C for up to 3 months. Suspensions were checked microscopically before each use to ensure 

even dispersion and the presence of at least 90 percent spores. 

To prepare freezer stocks for non-spore-forming bacteria, cultures of Bu. cepacia, S. Typhi, and V. cholerae were 

grown overnight and F. tularensis for 3 days in tryptic soy 

broth (TSB). After incubation, cell suspensions were stored at 

-70°C, amended with 30 percent sterile glycerol. To prepare 

slants, thawed stock cultures were transferred to TSA and 
Methods of Study 5

incubated for the specified times listed above. Fresh slant cultures were reinoculated weekly and the cultures used to seed 

the water samples did not exceed four generations. Refrigerated slants were transferred to fresh TSA slants for seeding 

drinking-water samples—overnight cultures for Bu. cepacia, 

S. Typhi, and V. cholerae, and 3-day cultures for F. tularensis.

Viable C. parvum oocysts were flow-counted at the 

USEPA, Cincinnati, Ohio, using a BD FACSaria (Becton, 

Dickinson and Co.) flow cytometry system equipped with 

BD CloneCyt software; the procedures are described in detail 

elsewhere (Francy and others, 2004). The oocysts were flowcounted to achieve the target number (10,000 oocysts for the 

composite seed and qPCR controls and 100 oocysts for IMS 

controls) and suspended in 1 mL of 0.01 percent Tween 20 

in 50-mL conical test tubes. The flow-counted tubes were 

shipped to the USGS by overnight mail and stored at 4°C for 

up to 2 weeks. 

 The seed inoculum was prepared by adding a 1-μl loopful of Bu. cepacia, S. Typhi, and V. cholerae and two 1-μL 

loopfuls of F. tularensis into separate 1- mL aliquots of PBS. 

Appropriate dilutions of each organism and of a B. anthracis

spore suspension were prepared in 1:10 increments in PBS. 

To prepare the composite seed, 0.9 mL of the 10-4 dilution 

of B. anthracis, Bu. cepacia, S. Typhi, and V. cholerae were 

added into the tube containing flow-counted C. parvum; for F. 

tularensis, 0.9 mL of the 10-3 dilution was added. Aliquots of 

the composite seed were removed before seeding the samples 

and were enumerated by cultural, IMS/FA, and qPCR methods 

to obtain pre-UF concentrations. 

Traditional Methods

Primary isolation and confirmation procedures for each 

target bacterial agent are described below and are based on 

American Society for Microbiology and others (2001−8) for B. 

anthracis, Bu. pseudomallei (Bu. cepacia), and F. tularensis and 

American Public Health Association and others (1998, Section 

9260) for S. Typhi and V. cholerae. Preliminary testing, when 

needed, was done using Columbus, Ohio, tap water to select the 

best primary isolation procedure based on recovery of the target 

organism and utility of the method. For each bacterial agent, 

dilutions of the composite seed, seeded retentate (aliquot obtained 

after UF of each seeded water sample), and unseeded retentate 

(aliquot obtained after UF of each unseeded water sample) were 

made in order to enumerate each agent using primary isolation 

procedures. Plates were wrapped in parafilm and incubated for a 

specified time period. Plates were exposed to air every 24 hours 

to maintain aerobic conditions. Confirmatory tests of seeded 

retentates were done by selecting three or four isolates from each 

primary isolation agar and transferring each isolate to secondary 

agar—TSA (or TSA+SB for B. anthracis). For unseeded retentates, any suspected target colony was transferred to secondary 

agar for confirmation. For each media type and confirmatory test, 

control organisms and blanks were used to ensure proper identification of each target organism and media sterility. 

For primary isolation of B. anthracis, appropriate dilutions of sample were heat-treated at 70°C for 60 minutes, 

spread-plated onto polymyxin-lysozyme EDTA-thallous 

acetate (PLET) agar (Hardy Diagnostics, Santa Maria, Calif.) 

(Knisely, 1966), and incubated at 37°C. Colonies were 

enumerated after 2 days of incubation on PLET; B. anthracis

colonies were circular cream-white colonies with a groundglass texture. Confirmation tests included the identification of 

thin, long, Gram+ rods, often appearing in chains, and negative results for b-hemolysis on PLET and motility on motility test medium (Becton, Dickinson and Co.). Preliminary 

testing compared PLET with TSA+SB as primary isolation 

media. Although recoveries were similar by use of PLET and 

TSA+SB (data not shown but are available from the USGS 

Ohio Water Science Center in Columbus), PLET was used 

because plates were easier to read than TSA+SB plates. For 

TSA+SB, large colonies led to difficulties in discerning individual colonies and obtaining accurate colony counts. 

For Bu. cepacia, the selected primary isolation medium 

was Burkholderia cepacia Selective Agar (BCSA) (Hardy 

Diagnostics) (Henry and others, 1997), incubated at 35°C. 

Because previous research showed that Bu. pseudomallei 

grew as well on BCSA as on Ashdown’s Medium (Peacock 

and others, 2005), BCSA was selected as the primary isolation 

media. Colonies were enumerated after 3 days of incubation 

on BCSA; Bu. cepacia colonies showed variable morphology, 

from small and dry to moist and large; appearing from purple 

to purple gray, some with yellow or pink zones in the medium 

surrounding the colony. Confirmation tests for Bu. cepacia

included the identification of short, Gram– rods or coccobacilli; positive tests for catalase, oxidase (may be weak), and 

motility; a negative test for indole; and resistance to Colistin 

but with slight susceptibly to Polymyxin B. Confirmatory test 

results are the same for Bu. pseudomallei, with the notable 

exception of Bu. psuedomallei being resistant to Polymyxin B. 

For F. tularensis, the selected primary isolation medium 

was Cystine Heart Agar supplemented with hemoglobin, 

antibiotics, and blood (CHA+B) (Remel, Lenaxa, Kans.), 

incubated at 35°C. Francis (1928) originally developed blood 

dextrose cystine agar, which was later modified by Shaw 

(1930) and Rhamy (1933) to CHA+B. Colonies were enumerated after 7 days of incubation on CHA+B; F. tularensis

colonies were gray white, 1 to 3 mm in diameter, round, flat, 

and smooth, with a characteristic sheen when viewed under 

indirect light. F. tularensis colonies were large enough to 

count accurately only after 4−7 days of growth; colonies larger 

than a pinpoint before 48 hours were not recorded as positive 

for F. tularensis. During this long incubation time, colonies 

of Bu. cepacia would sometimes appear on CHA+B and 

mask the growth of slower-growing neighboring F. tularensis

colonies. Because Bu. cepacia growth preceded F. tularensis

growth with the potential to interfere with enumeration of F. 

tularensis, the concentration of F. tularensis in the composite 

seed was increased. As a result, F. tularensis colonies were 

sometimes too numerous to count with the usual precision, 

and calculated concentrations and percent recoveries were 
6 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

expressed as estimated values. Confirmation tests for F. tularensis included the identification of tiny, pleomorphic Gram– 

coccobacilli; a positive test for catalase; and negative tests for 

oxidase and urease.

For S. Typhi, a five-tube most-probable number (MPN) 

pre-enrichment (10-1 to 10-5 dilutions) was prepared in 9 mL 

of buffered peptone water (BPW) (Hardy Diagnostics) and 

incubated at 37°C for 18 to 24 hours. An inoculum from each 

BPW tube was then transferred to an MPN enrichment tube 

containing Rappaport-Vasiliadis broth (RV) (Becton, Dickinson, and Co.). After incubation at 43°C for 18 to 24 hours, 

an aliquot from each RV tube was streaked onto part of a 

BBL CHROMagar plate (Becton, Dickinson, and Co.) and 

incubated at 35°C for 48 hours. Positive S. Typhi colonies 

on BBL CHROMagar were magenta to purple. Confirmation 

tests for S. Typhi included the identification of Gram– bacilli; 

a red slant, acid butt, and black precipitate on triple sugar iron 

agar (TSI) (Becton, Dickinson, and Co.), indicating lactose, 

sucrose, and dextrose fermentation and H2

S production; and 

VP negative and MR positive on Methyl Red–Vogues-Proskauer Broth (MR/VP), indicating the presence of acetoin and 

acidity of metabolic end products.

Several other primary isolation agars were tested for S. 

Typhi before selection of BBL CHROMagar. They included 

bismuth sulfite (BS), Hektoen enteric agar (HE), Miller-Mallinson agar (MM), and Xylose lysine tergitol 4 agar (XLT-4) 

(BS, HE, and MM are manufactured by Becton, Dickinson and 

Co.; XLT-4 is manufactured by Hardy Diagnostics). Colonies 

of S. Typhi on BBL CHROMagar, originally developed by 

Rambach (1990), were bright magenta and easily distinguishable from nontarget colonies. Other mentioned media were 

excluded from use for the following reasons:

• BS did not recover as many organisms as HE.

• V. cholerae was also able to grow on HE, potentially 

interfering with enumeration of target colonies.

• MM medium relied on H2S production for identification of target colonies. Some colonies of the positivecontrol organism did not produce H2

S on MM agar, 

and the H2S indicator (black color within colonies) 

often faded with extended incubation.

• Growth of the positive-control organism on XLT-4 did 

not produce enough H2S to distinguish it from nontarget colonies.

For V. cholerae, a five-tube MPN enrichment (10-1 to 10-5

dilutions) was prepared in 9 mL of alkaline peptone water 

(APW) (Remel) and incubated at 37°C for 18 to 24 hours. 

An aliquot from each APW tube was streaked onto part of a 

thiosulfate citrate bile salt sucrose agar plate (TCBS) (Remel), 

incubated at 35°C for 72 hours, and enumerated by use of 

MPN tables. Positive V. cholerae colonies on TCBS were 

large, smooth, yellow, and slightly flattened, with opaque centers and translucent peripheries. Confirmation tests for V. cholerae included the identification of Gram– straight or curved 

rods; a yellow slant and butt without a black precipitate on 

TSI; a positive string test (cells lyse and DNA forms a string 

in the presence of sodium desoxycholate); a positive oxidase 

test; and agglutination with Polyvalent O1 antiserum. 

Presumptive colonies of S. Typhi and V. cholerae in 

the unseeded retentate of one sample were sent to the USGS 

National Wildlife Health Center in Madison, Wis., for identification by means of a semiautomated microbial identification 

system with a 96-well format (Biolog Inc., Hayward, Calif.). 

The IMS/FA method for C. parvum was performed 

as described in USEPA Method 1623 (U.S. Environmental 

Protection Agency, 2005) with some modifications. Briefly, a 

Dynabeads anti-Cryptosporidium IMS kit (Invitrogen Corp., 

Carlsbad, Calif.) was used to separate oocysts from other 

particulates. A major modification was that the dissociation 

of the bead oocyst complex was done with heat, not acid, as 

described in Ware and others (2003). Following IMS, samples 

were transferred to well slides (Meridian Bioscience Inc., Cincinnati, Ohio) and dried in a desiccating chamber overnight. 

The slides were stained with a fluorescein-labeled monoclonal 

antibody, Crypt-a-Glo (Waterborne, Inc.), and counterstained 

with 4′,6-diamidino-2-phenylindole dihydrochloride hydrate 

(DAPI) (Sigma-Aldrich, D-9542). After the slides were 

stained, mounting media containing 1,4-diazabiclyclo (2,2,2) 

octane (Sigma-Aldrich, D-2522) was applied with a cover 

slip. The slides were microscopically examined within 7 days 

of staining. For all seeded samples, at least five oocysts were 

confirmed by DAPI. Positive and negative IMS and stain controls were included with each set of samples, processed and 

analyzed as described in Francy and others (2004). 

Molecular Methods

Initial Processing and DNA Extraction 

Before analyzing samples by qPCR, initial processing and DNA extraction steps were completed, as described 

in Francy and others (in press). Briefly, aliquots from the 

composite seed and the unseeded and seeded retentates were 

filtered through 0.4-μm polycarbonate filters (Whatman 

Inc., Florham Park, N.J.) and processed using the MO BIO 

PowerSoil DNA extraction kit (MO BIO Laboratories, Inc., 

Carlsbad, Calif.). DNA extraction was done using a modified 

version of the PowerSoil kit, in order to maximize recoveries 

(Francy and others, in press). The final extraction volume for 

each sample was 100 μL. All DNA extracts were stored at 4°C 

until qPCR analysis; all qPCR analyses were done within 24 

hours of DNA extraction.

Quality-control samples included DNA extraction blanks, 

DNA extraction positive controls, and matrix spikes; all were 

filtered and extracted as described above. DNA extraction 

blanks contained 10 mL of PBS. DNA extraction positive 

controls and matrix spikes both contained positive-control 

organisms: 100 μL of the 10-2 or 10-3 dilutions of B. anthracis, Bu. cepacia, F. tularensis, and V. cholerae and 10,000 
Methods of Study 7

flow-counted C. parvum oocysts. For DNA extraction positive controls, positive-control organisms were added to PBS, 

whereas for matrix spikes, positive-control organisms were 

added to an aliquot of the unseeded retentate. 

Quantitative PCR

Quantitative PCR reactions were carried out in optical 

96-well reaction plates in an Applied Biosystems 7500 RealTime PCR System (Applied Biosystems, Foster City, Calif.). 

Assays were optimized by Edgewood Chemical Biological Center (ECBC) (Francy and others, in press). Reaction 

mixtures contained 12.5 mL of the 2X TaqMan Universal 

PCR Master Mix (Applied Biosystems), 5 mL of DNA extract 

template, 0.3 or 0.4 mL of the primers and probes in order to 

achieve the concentrations listed in table 2, and moleculargrade water. Thermal cycling conditions were as follows: 

2 minutes at 50°C, 10 minutes at 95°C, and 45 cycles of 5 

seconds at 95°C and 31 seconds at 60°C. 

Primers and probes were selected for a variety of targets 

(table 2). A qPCR assay for S. Typhi was not available during 

the sampling period. One qPCR assay was used for C. parvum,

and two qPCR assays were used for the other four bacterial 

agents. For B. anthracis, Bu. cepacia, and V. cholerae, one 

Table 2. Primer and probe sequences for biological agents, final concentrations, and targets for each assay. 

[ Table modified from Francy and others (in press). Assays in italics and bold were expected to be positive for the laboratory-seeded strain. Assays developed 

by Dr. Sanjiv Shah, Edgewood Chemical Biological Center, Aberdeen Proving Ground, Md. μM, micromolar. ]

Organism Primer or probe Sequence

Concentration 

(μM)

Target

GenBank 

Accession 

Number

B. anthracis BA1 forward primer GCGGATAGCGGCGGTTA 0.3 Protective antigen 

gene (pagA)

AF268967

BA1 reverse primer TCGGTTCGTTAAATCCAAATGC 0.3

BA1 probe ACGACTAAACCGGATATGACATTAAAAGAAGCCCTTAA 0.3

BA2 forward primer TGCGCGAATGATATATTGGTTT 0.3 Capsular antigen gene 

(capB)

M24150

BA2 reverse primer GCTCACCGATATTAGGACCTTCTTTA 0.3

BA2 probe TGACGAGGAGCAACCGATTAAGCGC 0.3

Bu. cepacia* BC1 forward primer TCGACGCAGAACCTGAACAA 0.3 Motor rotation gene 

(motB)

AY536437

BC1 reverse primer GACTTGCGGTTCAGCACGAT 0.3

BC1 probe CGGACCCGCTCGATCCGGAG 0.3

BC2 forward primer ACGTCGATTCGTTCGTGTTCTT 0.3 Maltose binding protein gene (malE)

AF274304

BC2 reverse primer CAAGCTGAATTGCTCCTGGAA 0.3

BC2 probe CGCCAAGACGATCATGACGCCC 0.3

Cryptosporidium 

spp.

CP1 forward primer GATCACTATTACTAACGATAAGGGTAGATTATCA 0.4 70 kDa Heat shock 

protein gene 

(hsp70)

AB104730

CP1 reverse primer TGCTCATCCTCACCCTTGTATTT 0.4

CP1 probe AGGACGATATTGAACGTATGGTTAATGATGCTGA 0.3

F. tularensis FT1 forward primer AACAATGGCACCTAGTAATATTTCTGG 0.3 Outer membrane protein gene (fopA)

AF097542

FT1 reverse primer CCACCAAAGAACCATGTTAAACC 0.3

FT1 probe TGGCAGAGCGGGTACTAACATGATTGGT 0.3

FT2 forward primer ATTACAATGGCAGGCTCCAGA 0.3 17 kDa Protein gene 

(tul4)

AY219239

FT2 reverse primer GCCCAAGTTTTATCGTTCTTCTCA 0.3

FT2 probe TTCTAAGTGCCATGATACAAGCTTCCCAATTACTAAGTA 0.3

Vibrio spp. VC1 forward primer TCACGATGTCCAACCGTGAT 0.3 V. cholerae 23S 

rRNA gene

AE004341

VC1 reverse primer GCGGTCTCCTCCCAAAGAGT 0.3

VC1 probe AGCCCACCTTCGTGCTCCTCCG 0.3

VC2 forward primer AAATTGTGCGTATCAGCCTAGATG 0.4 V. cholerae hemolysin 

gene (hlyA)

M36855

VC2 reverse primer CGATAACCGAGTTGATCATTCAGA 0.4

VC2 probe TGACAGCACGGGAGCCGGC 0.4

* Primers and probes were designed for Bu. pseudomallei but were shown to react with Bu. cepacia.
8 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

assay was expected to be positive for the laboratory-seeded 

organism, and the second assay was expected to be negative 

because it targeted an agent-specific virulence-factor gene. For 

F. tularensis, both assays were expected to be positive with the 

laboratory-seeded strain. 

Quality-control samples for qPCR are described in 

Francy and others (in press). Quality-control samples included 

DNA extraction blanks (10 ml of PBS), DNA extraction positive controls (positive-control organisms added to duplicate 

aliquots of PBS), matrix spikes (positive-control organisms 

added to duplicate aliquots of unseeded retentates), qPCR 

positive controls, and no template controls (NTCs). The DNA 

extraction blanks, qPCR positive controls, and no template 

controls (NTCs) were run as single reactions. For qPCR positive controls, DNA extracts from each organism’s standard 

curve (known to produce detectable levels of fluorescence) 

were used as DNA templates. For NTCs, molecular-grade 

reagent water was used instead of DNA template. All samples 

were run by qPCR in triplicate.

Standard curves were developed for each assay before 

and during the sample-collection and analysis period (Francy 

and others, in press). Briefly, six dilutions of each organism 

were prepared and extracted separately and by two different 

analysts in order to fully characterize the variability in the 

extraction step. For C. parvum, each dilution used to prepare the standard curve was flow-counted separately by the 

USEPA. Concentrations of each organism were determined by 

cultural or microscopic methods as described above.

Data Analysis and Statistics

For S. Typhi and V. cholerae, MPN results were computed as described in American Public Health Association and 

others (1998, Part 9221 C). For culture or IMS/FA methods, 

numbers of organisms in composite seeds and seeded retentates were adjusted per volume analyzed. For cultural or IMS/

FA results, if an organism was not found in the seeded retentate, the lower detection limit was used. The lower detection 

limit was calculated by assuming that one organism was found 

in the undilute seeded retentate, and this value was used to 

calculate a less-than number. Recoveries of bacterial organisms by culture methods or C. parvum oocysts by IMS/FA 

were calculated by dividing the number of each microbe in the 

seeded retentate (including less-than values) by the number in 

the composite seed and multiplying by 100. 

The numbers of organisms found by qPCR in seeded 

retentate samples were determined from standard curves and 

then adjusted per volume analyzed. Cycle threshold (Ct) 

values from the standard curves were plotted against log10

concentrations for each assay. Regression analysis was done, 

and the resulting equation was used to interpolate unknown 

sample results for each biological agent. Ct values less than 40 

were considered detections of the target organism in this study. 

Ct values greater than 40 were qualified as detected with the 

possibility of a false-positive result. Recoveries of organisms 

by qPCR were not calculated because of the uncertainty of Ct 

values greater than 40 and problems with quantifying organisms by qPCR in the composite seed. 

In addition, the 95-percent confidence interval for each 

standard curve regression (SAS, Inc., Cary, N.C.) was used to 

provide a measurement of the level of uncertainty associated 

with predicting concentrations from qPCR results. Matrixspike and positive-control samples were used during processing of samples to determine matrix inhibition and DNA extraction efficiency. These data points were plotted on the standard 

curve to demonstrate consistent performance of each assay 

during each qPCR run. Specifically, this was determined by 

identifying whether the data points were within the 95-percent 

confidence interval for the standard-curve regression.

Pearson’s correlation coefficients were used to describe 

the strength of the association between recoveries of organisms 

by culture or IMS/FA and water-quality characteristics. Linear 

regression analysis was used to predict numbers of organisms 

found by traditional methods from numbers found by qPCR.

Analytical Results and Method 

Performance

Water Quality

Thirteen drinking-water samples were collected from 

nine water-treatment plants from February 2007 to February 

2008 (table 1). For surface-water sources, one sample was 

collected from each of four sites, and three samples were collected from one site (site 3). For ground-water sources, one 

sample was collected from each of two sites (raw or finished), 

and two samples were collected from each of another two sites 

(raw and finished). During repeat sampling at site 3, although 

pH was consistently high, specific conductance, alkalinity, 

hardness, and DOC were higher in the third sample than in 

the other two samples. In repeat samplings at the two groundwater sites (sites 2 and 4), water-quality characteristics were 

different because raw or finished water was collected. 

Wide ranges of water-quality values were found among 

sites. The pH ranged from 6.4 at site 6 (raw ground water) to 

9.7 at site 3 (surface water). Specific conductance ranged from 

249 mS/cm at site 3 to 1,321 mS/cm at site 8 (finished ground 

water). Water from site 8 also had the highest turbidity—2.1 

NTU. Alkalinities were low to moderate, except for 262 mg/L 

at site 2 and 201 mg/L at site 4 (both were raw ground water). 

Hardness ranged from 81 mg/L at site 3 (surface water) to 375 

mg/L at site 2 (raw ground water). Dissolved organic carbon 

concentrations were all below 2.0 mg/L, except at site 5 and 

one sample at site 3 (both surface water). Total coliforms were 

found at sites 2 and 4 (both raw ground water) in concentrations ranging from 1 to 8 CFU/100 mL; all samples were 

negative for E. coli. 
Analytical Results and Method Performance 9

Standard Curves and Variability of Molecular 

Results

Table 3 shows performance characteristics for each 

standard curve for the assays expected to be positive by using 

laboratory-seed strains. The dynamic range of the standard 

curve is the lowest and highest concentrations of the standards 

that were used in the regression analysis. Variability in the 

DNA extraction step was included in standard-curve development by diluting the organisms and extracting each dilution, 

rather than extracting one concentration and then diluting that 

one extraction. As seen in an example standard curve for Bu. 

cepacia (fig. 1), variability around each concentration could 

be high (±4 Ct), based on the 95-percent confidence intervals. 

For example, a Ct of 30 would give a predicted Bu. cepacia

concentration of 132,000 with upper and lower confidence 

limits of 1,030,000 and 16,800, respectively. On the basis of 

data from standard curves, Ct values less than 40 were considered detections of target organisms in this study, Ct values 

>40 were considered +/- detections, and results with no qPCR 

signal were considered nondetections.

Microbial Recovery and Detection

Different levels of biological agents were present in the 

composite seed for inoculation into 100-L water samples (table 

4). The highest median seed values were for F. tularensis and 

V. cholerae. Wide ranges of composite seed numbers were 

used for all organisms except for C. parvum oocysts, which 

were prepared by flow cytometry. Recoveries for culture or 

IMS/FA methods for organisms seeded into drinking-water 

samples are listed in table 5. Recoveries were highly variable between samples and, in a few cases, were even variable 

between replicate pairs of the same sample (replicate pairs are 

shaded in table 5). Correlation analysis of the data summarized 

in table 4 indicated that seed level did not have an effect on 

recovery for any pathogen except for S. Typhi (data not shown 

but are available from the USGS Ohio Water Science Center 

in Columbus). For S. Typhi, as seed concentration increased, 

recovery decreased (r=-0.505, p=0.0388). 

The qPCR data are presented in table 5 as detected (+), 

not detected (-), or detected with a Ct >40 (+/-) in the seeded 

retentate. As expected, the laboratory-seed strains were always 

negative by qPCR for assays B. anthracis 2, Bu. cepacia 1, 

and V. cholerae 2; these results are not included in table 5. 

Recoveries by qPCR were not calculated because, for several 

samples, organisms were detected in the seeded retentate (after 

UF) but not detected in the composite seed (before UF). It was 

therefore concluded that the quantification of organisms in the 

composite seed by qPCR was unreliable. There were other 

problems with the qPCR method. There were many nondetections or +/- detections by qPCR in samples 3, 4, 10, and 11. 

For samples 3 and 4, results from seeded samples and positive-control samples were unexpectedly low or not detected. 

Table 3. Performance characteristics of quantitative 

polymerase chain reaction (qPCR) standard curves for each 

assay. 

[Table from Francy and others (in press)] 

Assay Slope y-intercept R2 Dynamic range

B. anthracis 1 -4.39 50.9 0.913 1,200–1,200,000

Bu. cepacia 2 -4.86 54.9 0.901 910–9,100,000

C. parvum 1 -3.12 47.9 0.876 1,000–100,000

F. tularensis 1 -3.97 51.0 0.880 660–66,000,000

F. tularensis 2 -4.09 53.7 0.830 660–66,000,000

V. cholerae 1 -4.63 49.8 0.941 130–13,000,000

15

20

25

30

35

40

45

50

2 3 4 5 6 7 8

Cycle threshold (Ct) value

Log10 colony-forming units per 100 milliliters

Figure 1. Standard-curve plot of the cycle-threshold value 

versus log10-transformed concentrations of Burkholderia cepacia 

as determined by cultural methods.

Table 4. Numbers of colony-forming units for bacteria or 

oocysts for C. parvum used to seed 100-liter water samples 

as determined by culture or immunomagnetic separation/

fluorescence antibody (IMS/FA) methods.

Organism Minimum Maximum Median

B. anthracis 367 30,400 11,800

Bu. cepacia <33 49,100 10,350

C. parvum 2,310 5,570 3,840

F. tularensis 8,250 1,040,000 197,000

S. Typhi 12,100 264,000 86,900

V. cholerae 869 594,000 187,000
10 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

Samples 3 and 4 were reextracted and run by qPCR, and similar results were obtained. It was hypothesized that primer and 

probe reagents had begun to degrade; therefore, new reagents 

were purchased, and subsequent sample and quality-control 

results were as expected. Samples 10 and 11 were processed 

by using a DNA extraction kit lot number that was later shown 

to be inefficient in extracting the DNA and was the cause of 

nondetections by qPCR. In separate tests, statistically significant differences in qPCR results for three qPCR assays (B. 

anthracis, F. tularensis, and V. cholerae) were found by using 

different reagent lot numbers of the DNA extraction kit (data 

not shown but are available from the USGS Ohio Water Science Center in Columbus).

Recoveries of B. anthracis ranged from 4.1 to 87.3 

percent for the culture method. Recoveries for replicate pairs 

were generally in the same range except for the 39 to 82.6 

percent replicate pair for sample 12. Suspect Bacillus colonies 

were found on PLET (primary isolation medium) from one 

unseeded retentate sample (sample 11); the organism was 

later confirmed as nontarget growth and was not B. anthracis

(the colony had atypical morphology on secondary agar and 

was motile). The qPCR method detected B. anthracis in all 

14 samples with results, providing a +/- detection in only 1 

sample. 

Recoveries of Bu. cepacia for the culture method ranged 

from less than detection to 52.5 percent and were generally in 

the same range for replicate pairs. A large number of recoveries, however, were below detection for the culture method. 

Bu. cepacia recoveries in samples 1−3 were moderate (10.2 

to 29.6 percent) but decreased to very low percentages in 

samples 4−6 (<1.0 to 1.8 percent). For sample 7, a new culture 

stock was ordered from the supplier. Recoveries increased 

somewhat but were still low for sample 7 (5.4 percent) and 

sample 8 (5.3 and <0.5 percent). For sample 9, in an attempt 

Table 5. Recoveries by culture (for bacteria) or immunomagnetic separation/fluoresence antibody (IMS/FA) (for C. parvum) 

methods and detections by quantiative polymerase chain reaction (qPCR) after ultrafiltration of pathogens seeded into 100-liter 

water samples. 

[Table modified from Francy and others (in press). R, replicate sample (shading denotes field replicates); +, detected; -, not detected; +/-, detected, but 

Ct value was greater than 40; <, not detected at less than this value; ND, not determined.]

Sample # Site

Recoveries by culture or IMS/FA (percent) and detections by qPCR

B. anthracis Bu. cepacia C. parvum F. tularensis S. 

Typhi V. cholerae

CultureqPCR 

1

CultureqPCR 

2

Culture qPCR CultureqPCR

1

qPCR

2

CultureCultureqPCR 

1

1 1 87.3 + 10.2 + 46.5 +/- 6.3 + + 68.6 37.2 +

2 2 16.7 + 29.6 +/- 10.5 +/- 5.4 + + 396 55.2 +

2R 2 30.0 + 12.3 + 74.1 +/- 8.6 + + 96.1 88.7 +

3 3 21.4 NDb 22.4 NDb <2.2 NDb 1.0 NDb NDb 78.2 77.8 NDb

4 4 4.1 NDb 1.8a NDb 14.0 NDb 0.34 NDb NDb 4.6 12.8 NDb

5 5 40.0 + <22.4a + 105 + 20.2 + + 145 4.5 +

5R 5 54.1 + <28.6a + 84.2 + 21.7 + + 122 8.0 +

6 6 20.8 + <1.0a +/- NDb + 0.20 + + 4.1 11.6 +

7 7 28.4 + 5.4a + 87.6 +/- 13.0 + + 25.1 25.1 +

8 8 7.0 + 5.3a + 74.2 + 17.3 + + 16.7 145 +

8R 8 19.3 + <0.5a + 25.5 + 20.4 + + 371 11.9 +

9 9 13.7 + <0.4a -c 40.5 + 13.9 + + NDb NDb +

9R 9 19.5 + <0.3a -c 52.2 + 26.4 + + NDb NDb +

10 2 12.1 NDb <240a NDb 244 NDb 19.4 NDb NDb 71.7 11.0 NDb

11 3 49.3 NDb 52.5 NDb 71.5 NDb 23.1 NDb NDb 118 288 NDb

11R 3 34.8 NDb 27.4 NDb 77.3 NDb 33.0 NDb NDb 48.5 106 NDb

12 4 82.6 + 13.3 + 74.3 + 14.3 + + 45.7 79.7 +

12R 4 39.0 +/- 22.3 - 92.2 +/- 40.4 + + 129 39.3 +

13 3 43.7 + 28.9 + 103 + 30.1 + + 204 288 +

a

 Results were removed from subsequent data analysis because of possible temperature effects on culture.

b

 Not determined because results did not meet quality-assurance requirements.

c

 A different strain was used.
Analytical Results and Method Performance 11

to obtain better growth of Bu. cepacia, a different strain was 

ordered from the supplier (ATCC 17759). The new strain was 

reported to be motile and isolated from forest soil; the original 

strain was nonmotile but was also isolated from soil. The new 

strain was not detected by either culture or qPCR methods 

in sample 9. Returning to the original Bu. cepacia strain for 

sample 10, organisms were still not recovered by culture. For 

sample 11, water samples were kept overnight at room temperature and allowed to reach 17°C before seeding. (Samples 

were previously kept in the refrigerator overnight). For sample 

11, Bu. cepacia recoveries by the culture method were 52.5 

and 27.4 percent in replicates A and B, respectively. Samples 

12 and 13 were treated the same as sample 11, and recoveries 

were comparable. Out of 14 samples with results by qPCR, 9 

were positive, 2 were +/- detected, and 3 were negative (two 

of these negatives resulted from using a difference strain of Bu 

cepacia). In sample 12, Bu. cepacia was detected by qPCR in 

one replicate but not in the other replicate; for the nondetection by qPCR, the organism was detected by culture. In four 

samples, Bu. cepacia was detected by qPCR but was below 

detection for the culture method because of possible temperature effects described above. 

Recoveries for C. parvum ranged from below detection 

to 244 percent for IMS/FA. Recoveries for replicate pairs for 

IMS/FA were different in samples 2 and 8. For the IMS step 

alone, recoveries were less variable, ranging from 23 to 87 

percent with an average recovery of 65.4 percent (data not 

shown but are available from the USGS Ohio Water Science 

Center in Columbus). Of the 14 samples with results for C. 

parvum by qPCR, 9 were positive and 5 were +/- detected. For 

the samples with +/- detections, C. parvum was detected by 

IMS/FA. 

Recoveries for F. tularensis ranged from 0.2 to 40.4 percent for the culture method. Recoveries for replicate pairs for 

the culture method were generally in the same range, except 

for sample 12. F. tularensis was detected in all 14 samples by 

both qPCR assays. 

Recoveries for S. Typhi ranged from 4.1 to 396 percent 

for the culture method; samples were not analyzed for S. Typhi 

by qPCR. Recoveries for replicate pairs were highly variable; 

this was because cell counts were made using MPN estimates 

and not from direct plating methods. In sample 2, typical S. 

Typhi colonies were found on BBL CHROMagar (primary 

isolation medium) from the unseeded retentate; these colonies 

were later confirmed as nontarget growth and identified as 

Pseudomonas maculicola. 

Recoveries for V. cholerae ranged from 4.5 to 288 percent 

for the culture method. As with S. Typhi culture results, cell 

counts were made using MPN estimates, and recoveries for 

replicate pairs were highly variable. V. cholerae was detected 

by qPCR in all 14 samples. It is important to note, however, 

that the V. cholerae qPCR assay resulted in a late but positive signal for the unspiked retentate of sample 2 (Ct=36.71). 

Positive signals for V. cholerae in all samples ranged from 

Ct=28.53 to Ct=37.89, with an average of Ct=31.11 (data 

not shown but available from the USGS Ohio Water Science 

Center in Columbus). In sample 2, suspect colonies on TCBS 

(primary isolation medium) in the unseeded retentate were 

later identified as non-Vibrio and members of the families 

Enterobacteriaceae or Pseudomanaceae. The qPCR assay 

for V. cholerae on pure cultures of the nontarget isolate from 

TCBS and the nontarget isolate on BBL CHROMagar (mentioned in the previous paragraph on S. Typhi) resulted in a late 

signal for the TCBS isolate (Ct=39.31) and a >40 Ct for the 

BBL CHROMagar isolate.

The relations between sample water-quality characteristics and associated recoveries are listed in table 6 as a 

median recovery of all bacteria combined, for individual 

bacterial pathogens, and for C. parvum. The C. parvum data 

are presented separately because analysis was done by IMS/

FA. For all bacterial data combined, significant (relations were 

considered significant if p<0.1) positive correlations were 

found between median recoveries by culture methods and 

pH or DOC, and a significant negative correlation was found 

between recoveries and specific conductance. For Bu. cepacia, 

none of the relations were significant because of a small dataset. The relations between water-quality characteristics and S. 

Typhi recoveries did not follow a pattern similar to those of 

the other bacterial pathogens (that is, the correlation was positive for S. Typhi when it was negative for other organisms). 

No significant relations were found between IMS/FA recoveries and any water-quality characteristic measured. 

Comparison of Number of Organisms Detected 

by Traditional and Molecular Methods 

The data representing the linear-regression relations 

between qPCR and culture or IMS/FA numbers in seeded 

retentates are shown for each organism in figure 2. The slope 

of the regression line is a measure of the rate of change in culture or IMS/FA numbers with change in qPCR numbers. The 

slopes were positive and significant (at p<0.05) for B. anthracis and F. tularensis and were nearly significant for V. cholerae

(p=0.1018). Among these three organisms, the slope was highest for V. cholerae. For Bu. cepacia, although the coefficient 

of determination of the regression was moderate (R2

=0.39), 

the slope was not significant because of the small dataset. The 

relations between IMS/FA and qPCR results for C. parvum

were not significant, and the regression line was essentially 

flat. For F. tularensis, the relation was stronger (R2 values 

were higher and slopes were more significant) between culture 

results and qPCR assay 1 than qPCR assay 2. More insight 

can be gained by examining the placement of 1:1 lines as 

compared to linear regression lines. For B. anthracis and to a 

lesser extent, for Bu. cepacia, the regression line was near the 

1:1 line. For F. tularensis, both assay regressions were strongly 

influenced by one data point and qPCR numbers were biased 

high over culture numbers. In contrast, for V. cholerae, culture 

numbers were considerably higher than qPCR numbers. 
12 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

Table 6. Pearson’s r correlations between water quality and recoveries of biological agents. 

[Relations that were significant at p<0.05 are in italics and bold: those at p>0.05 and <0.1 are in bold only]

All bacteria 

combined B. anthracis Bu. cepacia F. tularensis S.Typhi V. cholerae C. parvum

Number 19* 19 9 19 17 17 18

pH 0.498 0.192 0.415 0.630 0.086 0.593 -0.059

Specific conductance -0.438 -0.408 -0.521 -0.109 0.294 -0.131 -0.184

Turbidity -0.163 -0.142 -0.385 0.105 0.189 0.001 -0.113

Alkalinity -0.168 -0.241 -0.164 -0.479 0.214 -0.067 -0.306

Hardness -0.346 -0.394 -0.243 -0.411 0.240 -0.190 -0.326

Dissolved organic carbon 0.548 0.400 0.425 0.421 0.097 0.291 0.087

*

 Median values for recoveries of all bacteria combined for each sample.

0 3,000 6,000 9,000 12,000

0

3,000

6,000

9,000

12,000 B. anthracis

y = 1.16x + 320

R2

 = 0.79

0 4,000 8,000 12,000 16,000

0

4,000

8,000

12,000

16,000 Bu. cepacia

y = 0.42x+ 2,500

R2

 = 0.39

0 1,000 2,000 3,000 4,000 5,000

0

1,000

2,000

3,000

4,000

5,000

C. parvum

Cultural or IMS/FA number

y = -0.28x+ 2,500

R2

 = 0.006

0 10,000 20,000 30,000 40,000

0

100,000

200,000

300,000

400,000 V. cholerae

y = 4.06x+ 6,800

R2

 = 0.24

0 300,000 600,000 900,000

0

300,000

600,000

900,000 F. tularensis 1

Figure 2. Regression relations for qPCR and culture or IMS/FA numbers for seeded retentate 

samples. (Slopes in bold were statistically significant at δ = 0.05.)

y = 0.34x + 5,200

R2

 = 0.74

0 300,000 600,000 900,000

0

300,000

600,000

900,000 F. tularensis 2

Seeded retentate

1:1 line

y = 0.40x - 2,400

R2

 = 0.60

EXPLANATION qPCR estimated number

Figure 2. Regression relations for quantiative polymerase chain reaction (qPCR) and culture or immunomagnetic 

separation/fluoresence antibody (IMS/FA) numbers for seeded retentate samples. Slopes in bold were statistically 

significant at alpha = 0.05. (Figure modified from Francy and others, in press.)
Summary and Conclusions 13

Suggestions for Future Study

• Effects from physical and chemical components of 

water matrices on recoveries by qPCR could be further 

investigated. Because qPCR recoveries could not be 

reliably calculated in this study, the effects of water 

quality on qPCR recoveries could not be determined. It 

is well known, however, that water matrices may contain organic and inorganic substances with the potential 

to inhibit PCR (Wilson, 1997). These include humic 

and phenolic compounds, both contributors to DOC. 

•	 The specificity for the V. cholerae qPCR assay needs to 

be further investigated. Suspect target colonies, later 

confirmed as nontarget growth, were found in one of 

the unseeded retentate samples for S. Typhi and V. 

cholerae. The V. cholerae qPCR assay provided late, 

but positive results for these isolates. The assay, which 

targets the 23S rRNA gene, is, therefore, not 100 percent specific for V. cholerae.

•	 More testing would need to be done to determine the 

ability of the primers and probes to detect different 

strains of Bu. cepacia. A second strain was not detected 

by the qPCR assay in this study.

• Additional work would be needed to increase qPCR 

detection rates for some of the target organisms. The 

qPCR method can be used to rapidly detect B. anthracis, F. tularensis, and V. cholerae with some certainty 

in drinking-water samples; however, additional work 

would be needed to optimize and test qPCR for Bu. 

cepacia and C. parvum. 

• For all organisms, additional research would be 

needed to reduce the variability of qPCR, including 

reducing variability of the DNA extraction procedure, 

and to determine minimum detection limits for qPCR 

assays. 

• A geographically widespread study is needed, especially in areas where F. tularensis and Bu. cepacia may 

be found in unseeded samples. 

Summary and Conclusions

Water supplies in the United States are potential targets 

for bioterrorists wanting to disrupt society or damage important parts of the infrastructure. To reduce the impact and 

consequences from an intentional contamination event with 

biological agents, methods are needed to rapidly detect the 

presence of these agents in drinking-water supplies. Ultrafiltration (UF) is a method that can be used to concentrate multiple 

microorganisms simultaneously from drinking water; however, after concentration, analytical methods are still needed to 

quickly detect their presence in the retentate. Because traditional cultural and microscopic methods take days before any 

confirmatory answer is available, molecular methods, such as 

quantitative polymerase chain reaction (qPCR), are considered 

a viable alternative. Minimal work has been done, however, 

to test qPCR for detecting biological agents in targeted testing 

of water samples and comparing results to that of traditional 

analytical methods. 

Thirteen drinking-water samples were collected from 

nine water-treatment plants in Ohio to assess performance 

of qPCR in comparison to traditional analytical methods for 

detection of biological agents. Two 100-L subsamples were 

collected at each site during each sampling event. One was 

seeded in the laboratory with six target organisms—Bacillus 

anthracis Sterne (“B. anthracis”), Burkholderia cepacia (as 

a surrogate for Bu. pseudomallei), Francisella tularensis Live 

Vaccine Strain (“F. tularensis”), Salmonella Typhi, Vibrio 

cholerae, and Cryptospordium parvum. Six replicate seeded 

samples were included to determine processing and analytical 

variability. The seeded and unseeded samples were processed 

by UF within 2 to 4 hours and analyzed by qPCR and by traditional culture methods for bacterial agents and by immunomagnetic separation/immunofluorescence microscopy assay 

(IMS/FA) for C. parvum. Specific conductance, temperature, 

dissolved oxygen, pH, turbidity, and alkalinity were measured 

and samples were collected and analyzed for dissolved organic 

carbon (DOC), calcium, and magnesium concentrations. Total 

coliform and E. coli concentrations were determined by use of 

a standard membrane-filtration method. 

Because the focus of the study was a comparison of 

methods, considerable time and effort was expended to 

identify and document the best methods and modifications 

needed for each target organism. For example, PLET agar was 

found to be superior to TSA+SB agar for primary isolation of 

B. anthracis, and BBL CHROMagar was selected over other 

agar methods for primary isolation of S. Typhi. The IMS/

FA method was used for C. parvum, with heat dissociation 

substituted for acid dissociation. DNA extraction steps were 

modified to optimize recoveries. The manufacturer’s protocol 

for the DNA extraction kit, which calls for the removal of a 

portion of the total volume during wash steps, was modified 

such that the entire volume was removed. Subsequent volume 

additions were adjusted accordingly.

Recoveries were calculated for culture or IMS/FA methods for different levels of organisms. Recoveries were highly 

variable between samples and were sometimes even variable 

between replicate pairs of the same sample. Recoveries ranged 

from 4.1 to 87.3 percent for B. anthracis, <0.3 to 52.5 percent 

for Bu. cepacia, <2.2 to 244 percent for C. parvum, 0.2 to 40.4 

percent for F. tularensis, 4.1 to 396 percent for S. Typhi, and 

4.5 to 288 percent for V. cholera. The most consistent recoveries among samples and for replicate pairs were obtained for F. 

tularensis. Wide ranges of recoveries were found for S. Typhi 

and V. cholera, even among replicate pairs; this was because 

cell counts were made by using MPN estimates. Recoveries 

of C. parvum by IMS/FA were also highly variable among 
14 Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

the different sites. This was not unexpected, because other 

researchers found a wide range of recoveries in stream and 

source waters (Francy and others, 2004; Kuhn and Oshima, 

2002; U.S. Environmental Protection Agency, 2001). Recoveries of bacterial agents by culture methods can be affected by 

loss of culturability, as shown by reduced recoveries of Burkholderia suspected to be caused by lower temperatures in this 

study. Although there are no available data for Bu. cepacia, it 

was reported that storing Bu. pseudomallei (the bacterial agent 

for which Bu. cepacia is serving as a surrogate) in a refrigerator converts a proportion of the bacteria to a nonculturable state 

(Inglis and Sagripanti, 2006). Further, investigators found that 

survival of Bu. pseudomallei was extended at temperatures 

of 24 and 32°C but not at lower temperatures. Indeed, the 

distribution of meliodosis, the disease caused by Bu. pseudomallei, is primarily limited to tropical and semitropical locations 

between latitudes 20°N and 20°S (Inglis and Sagripanti, 2006). 

The drinking-water samples included wide ranges of 

pH, specific conductance, alkalinity, and hardness, with narrower ranges of turbidity and DOC. Recoveries by the culture 

method for all bacteria combined were significantly related 

to pH, DOC (positive correlations), and specific conductance 

(negative correlation). Although these relations were not 

investigated further, it seems likely that pH, DOC, and specific 

conductance may affect the physiological state of the organisms and their potential to grow in culture. Recoveries by 

IMS/FA for C. parvum were not related to any water-quality 

characteristic. This is contrary to other reports in the literature 

where investigators found that the water matrix could affect 

recovery of C. parvum by use of IMS/FA; specifically, that 

recoveries were related to turbidity (Kuhn and Oshima, 2002; 

Francy and others, 2004) and pH (Kuhn and others, 2002). 

Recoveries by qPCR were not determined because in 

many of the qPCR results, there was a stronger signal in the 

seeded retentate than in the composite seed. This is contrary to 

conventional thinking because more organisms were recovered 

after UF than were seeded into the system. Possible explanations for enhanced detection after UF include poor extraction 

efficiency in the composite seed and (or) removal or dilution of inhibitors from the water sample during UF. Possible 

inhibitors to qPCR in the composite seed may have come from 

the C. parvum tube used to prepare the composite seed (0.01 

percent Tween) or from carryover from the agar media used 

to grow bacterial pathogens. Because of these limitations, 

organisms could not be accurately quantified by qPCR in the 

composite seed. In addition, the qPCR method is limited by 

the bias and variability inherent in many nucleic acid techniques (Lim and others, 2005). These include variability of 

DNA-extraction efficiencies. In this study, an inefficient DNA 

extraction kit lot resulted in removal of the qPCR results (most 

were nondetections) of samples 10 and 11 from the dataset. 

The suspected degradation of primers and probes led to a large 

proportion of nondetection by qPCR for samples 3 and 4, and 

they also were removed from the dataset. 

The qPCR results were reported as detected, not detected, 

or +/- detected (Ct values >40) in the seeded retentates. These 

are the samples that went through the UF procedure, so it 

is important from a practical standpoint to be able to detect 

these organisms in seeded retentates. Not including results 

from samples 3, 4, 10, and 11, F. tularensis and V. cholerae

were positively detected in all 14 samples. B. anthracis was 

detected in the seeded retentates of every sample except that 

it was only +/- detected in one of two replicates of sample 12. 

Detections of Bu. cepacia and C. parvum by qPCR in seeded 

retentates were more inconsistent. In sample 9, Bu. cepacia

was not detected, but a different strain was used. More testing 

would need to be done to determine the ability of the primers and probes to detect different strains of Bu. cepacia. It is 

important to note, however, that Bu. cepacia was positively 

detected by qPCR in 9 of 14 samples and was sometimes 

detected by qPCR and not by culture. Among the organisms 

tested, C. parvum qPCR results had the greatest number in 

which Ct was >40. C. parvum is present in an environmentally 

resistant form, the resilience of which may affect DNA-extraction efficiency. In addition, C. parvum was seeded in relatively 

low numbers, which may help to explain the large number of 

+/- detections by qPCR. Recoveries could not be reliably calculated in this study, so the effects of water quality on qPCR 

recoveries were not determined. 

The potential for false positive results also could be 

further investigated. Suspect target colonies, later confirmed as 

nontarget growth, were found in one of the unseeded retentate samples for S. Typhi and V. cholerae (sample 2) and one 

of the unseeded retentate samples for B. anthracis (sample 

11). Because the V. cholerae qPCR assay provided a late, but 

positive result in sample 2, this assay, which targets the 23S 

rRNA gene, is not 100 percent specific for V. cholerae. The 

nontarget, suspect growth on PLET in sample 11 suggested 

that PLET is not 100 percent specific for B. anthracis. In a 

study by Papaparaskevas and others (2004), investigators 

found that PLET was selective for B. anthracis by inhibiting 

two thirds of contaminating bacilli as well as other bacteria, 

but the specificity of PLET was low. The qPCR results for B. 

anthracis for sample 11 were not available. 

If qPCR were to be used to rapidly detect biological 

agents in drinking-water samples, it would be important to 

establish the relations between qPCR and traditional methods. 

Therefore, regression equations were developed to determine 

whether numbers from culture or IMS/FA methods could be 

predicted from numbers from qPCR in filtered water samples 

(seeded retentates). The slopes of the regression lines were 

significant for B. anthracis and both F. tularensis assays and 

nearly significant for V. cholerae. Although a positive slope 

was found for these relations for Bu. cepacia, the sample size 

was too small to be significant. For C. parvum; negative slopes 

and a low R2

 indicated that, even with additional testing, it may 

not be possible to define a significant relation. For B. anthracis

and Bu. cepacia, cultural numbers were similar to qPCR numbers. For V. cholerae, cultural numbers were about 10 times the 

qPCR numbers. For F. tularensis, the opposite was true; qPCR 

numbers were about twice the cultural numbers. F. tularensis
References Cited 15

cells may have been injured during UF and may have become 

nonculturable, but they were still detected by qPCR. 

In conclusion, this is the first known study to compare 

the use of traditional and qPCR methods to detect biological 

agents in large-volume drinking-water samples (Francy and 

others, in press). This study confirmed that the UF procedure 

can simultaneously concentrate bacterial and protozoan pathogens from a variety of 100-L drinking-water samples. Most 

important, if qPCR is used as a presumptive test for biological 

agents in drinking water, it is important to determine whether 

there are false negative results related to traditional methods. 

In this regard, only three samples were false negatives (all for 

Bu. cepacia); and even in several samples, Bu. cepacia was 

detected by qPCR but not by culture. The qPCR method can 

be used to rapidly enumerate B. anthracis, F. tularensis, and 

V. cholerae with some certainty in drinking-water samples; 

levels found by the qPCR method were significantly related to 

levels found by the culture methods for these organisms after 

UF. However, the specificity for the V. cholerae assay needs to 

be further investigated. Although Bu. cepacia and C. parvum

were detected by qPCR in the majority of samples analyzed, 

additional work would be needed to optimize and test qPCR for 

these organisms to reduce nondetections or +/- detections and 

establish relations to numbers by traditional methods. For all 

organisms, additional research would be needed to reduce the 

variability of qPCR, including reducing variability of the DNA 

extraction procedure. Minimum detection limits for qPCR and 

the influence of drinking-water quality on qPCR could also 

be investigated in future studies. A geographically widespread 

study would be needed, especially in areas where F. tularensis

and Bu. cepacia may be found in unseeded samples. 

Acknowledgments

We thank the water purveyors for providing access to 

their water-treatment plants, David Blehert (USGS National 

Wildlife Health Center, Madison, Wis.) for identifying nontarget isolates, Mark Wolcott (U.S. Army Medical Research 

Institute of Infectious Diseases, Ft. Detrick, Md., USA) for 

providing expertise and a protocol on Bacillus spore preparation, and Sanjiv Shah (U.S. Environmental Protection Agency) 

for information on the qPCR primers and probes. 

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