ken hyer, u.s. geological survey richmond, va

Ken Hyer, U.S. Geological SurveyRichmond, VA

Bacterial Source Tracking:Methods Comparison and

Field Application

WV Department of Environmental ProtectionWV Department of Environmental Protection

VA Dept of Conservation and RecreationVA Dept of Conservation and Recreation

Berkeley County, WVBerkeley County, WV

WV Department of AgricultureWV Department of Agriculture

CooperatorsCooperators

VA Department of Environmental QualityVA Department of Environmental Quality

Fairfax County, VAFairfax County, VA

Objectives for Talk

• Describe a methods comparison study that evaluated 7 source tracking methods.

• Describe a field application of BST and the associated quality control activities.

Bacteria Source TrackingBacteria Source Tracking

WaterSamples

SourceSamples

IsolatedE. coli

IsolatedE. coli

rRNAC

rRNAB

rRNAA

rRNADog

rRNAHuman

rRNAGoose

UNKNOWN KNOWN

BST Methods Comparison Study• Sampling in Berkeley County, West Virginia.• Involves researchers from across the nation and 3 different

USGS district offices (Melvin Mathes of WV and Don Stoeckel of Ohio).

• Five Genotypic Methods (and investigators)– Ribotyping using two different enzyme sets

(George Lukasik, Mansour Samadpour)– Pulsed-field Gel Electrophoresis

(West Virginia Department of Agriculture)– rep-PCR using two different primer sets

(Howard Kator, Don Stoeckel)• Two Phenotypic Methods (and investigators)

– Antibiotic Resistance Analysis (Bruce Wiggins)– Carbon Substrate Utilization (Chuck Hagedorn)

BST Methods Comparison Study

• Prominent sources of fecal pollution being considered (based on NRCS input for Berkeley County):

– Humans

– Cattle (beef and dairy)

– Chickens

– Swine

– Horses

– Dogs

– Canada Geese

– Deer

Methods Comparison - Study Design

• Collect feces from at least 20 individuals per source.

• Isolate and confirm a library of known E. coli from the fecal samples:– Total of 70-100 confirmed E. coli per source– Total known library size of 900 isolates

• Prepare a blind sample set comprised of 200 isolates that included three subsets:– 26 Replicates from the known library– 150 Fresh isolates from the 9 prominent sources– 24 Fresh isolates from sources that were not in the

original known library (mice, cats, raccoons, etc.)

Methods Comparison - Study Design

• Each researcher identified the source of each blind isolate.

• Results were scored and the following were considered for each method:– Accuracy of isolate identification – Precision (reproducibility of replicate isolate

analyses)– Robustness (isolates from sources not in the

library are identified as unknown)

Methods Comparison - Results

• In a general sense, we found that:-In this study, under these conditions…

-Most methods did not perform as well as we expected, based on published literature.

-Detailed study manuscript is in press at Environmental Science and Technology.

Results - Replicates

• The first 3 methods used discriminant analysis (DA), the other 4 used direct matching techniques.

• In scoring the replicates, the response “unknown” was considered incorrect (all isolates were in the known library).

• For each method, considering an 8-way source classification:-ARA: 6 of 26 (23% correct)-CUP: 6 of 25 (24% correct)-RT-HindIII: 3 of 23 (13% correct)-RT-EcoR1: 14 of 26 (54% correct)-PFGE: 24 of 24 (100% correct)-BOX-PCR: 17 of 26 (65% correct)-REP-PCR: 10 of 23 (43% correct)

Results - Accuracy

• For the accuracy subset, the response “unknown” was considered neutral (neither correct nor incorrect) – thus the number of isolates attempted is very important.


Results - Ringers• In scoring the ringers, the response “unknown” was considered

the only correct response because none of these isolates were in the library.

• None of the DA methods attempted to identify and reject ringers.


Reasons For Method Underperformance

• Inadequate library size or structure

• Temporal component in the source-library collection

• Presence of many repetitive subtypes (transient strains)

• Different statistical analyses may be needed

• Regardless of these possible reasons, the study clearly demonstrates the need for QA/QC and proofing of methods.

Methods Comparison - Conclusions

• This is only one of several ongoing comparison studies. It demonstrates that under these study conditions, none of these methods are performing at the levels we anticipated.

• We can offer these recommendations:-Perform considerable QA/QC in your BST work! This may

include (1) analyzing blind collections of known isolates, (2) use of multiple BST methods, and (3) the use of other tracers to support the BST work.

-Perform your QA/QC in such a way that you can detect if your method is working or failing.

Example of an Applied StudyExample of an Applied Study

1. Accotink Creek – Urban 1. Accotink Creek – Urban

11

2. Blacks Run – Mixed Urban/Agricultural2. Blacks Run – Mixed Urban/Agricultural

22

3. Christians Creek - Agricultural3. Christians Creek - Agricultural

33

Study Design

• Field Data Collection

– Water-sample collection

• Baseflow

• Stormflow

• Continuum

– Source sample collection

• Bacteria Source Tracking Analysis (Ribotyping)

Results of MST:Results of MST:By Individual ContributorBy Individual Contributor

Blacks RunBlacks Run

Christians CreekChristians Creek

Accotink CreekAccotink Creek

00

55

1010

1515

2020

2525

3030

3535G

oo

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oo

se

Hu

ma

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um

an

Do

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og

Du

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uck

Ca

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at

Se

a G

ull

Se

a G

ull

Ra

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on

Ra

cco

on

Ca

ttle

Ca

ttle

De

er

De

er

Ho

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Ho

rse

Po

ultr

yP

oul

try

Pe

rce

nt o

f Kn

ow

nP

erc

en

t of K

no

wn

Seasonal Patterns in MST Data:Seasonal Patterns in MST Data:Comparison of Warm and Cool SeasonsComparison of Warm and Cool Seasons

00

1010

2020

3030

4040C

attl

eC

attl

e

Hu

ma

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um

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Wa

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f Con

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utio

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erc

en

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ontr

ibu

tion

Warm (May-Sept)Warm (May-Sept)

Cool (Oct-March)Cool (Oct-March)

Validation of MST:Validation of MST:Human SignatureHuman Signature

Accotink CreekAccotink Creek Christians CreekChristians Creek Blacks RunBlacks Run

CaffeineCaffeine

00

0.050.05

0.10.1

0.150.15

0.20.2

0.250.25

Ca

ffein

e (

µg

/L)

Ca

ffein

e (

µg

/L)

CotinineCotinine

00

0.010.01

0.020.02

0.030.03

0.040.04

Co

tinin

e (

µg

/L)

Co

tinin

e (

µg

/L)

Validation of MST:Validation of MST:Poultry SignaturePoultry Signature

00

100100

200200

300300

400400

500500

1010 2020 3030 4040 5050 6060

Time (Hours)Time (Hours)

Dis

char

ge (

cfs)

Dis

char

ge (

cfs)

00

0.10.1

0.20.2

0.30.3

0.40.4

To

tal A

rse

nic

(µg/

L)

To

tal A

rse

nic

(µg/

L)

DischargeDischarge

ArsenicArsenic

OtherOther21.1%21.1%

OtherOther12.0%12.0%

Accotink Creek, BST ResultsAccotink Creek, BST Results

(N=279)(N=279)

DogDog13.3%13.3%

DogDog9.0%9.0%

DeerDeer1.4%1.4%

DeerDeer10.0%10.0%

Four Mile Run, BST ResultsFour Mile Run, BST Results

(N=278)(N=278)

WaterfowlWaterfowl38.7%38.7%

WaterfowlWaterfowl37.0%37.0%

RaccoonRaccoon5.4%5.4%

RaccoonRaccoon15.0%15.0%

Comparison of MST Results:Comparison of MST Results:Comparison of Accotink Creek and Four Mile RunComparison of Accotink Creek and Four Mile Run

HumanHuman20.1%20.1%

HumanHuman17.0%17.0%

Take Home Messages

1. Perform considerable QA/QC to ensure that you have confidence in your results.

2. Many different tools that can be applied to quality assure your BST data.

3. Under appropriate conditions, it appears BST can be used to successfully identify bacterial sources.

USGS Contact InformationUSGS Contact Information

Ken HyerKen Hyer1730 E. Parham Rd1730 E. Parham RdRichmond, VA 23228Richmond, VA 23228Email: Email: [email protected]: 804-261-2636Phone: 804-261-2636On the web: http://va.water.usgs.gov/On the web: http://va.water.usgs.gov/

mailto:[email protected]

ken hyer, u.s. geological survey richmond, va

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