Date post: | 19-Aug-2015 |
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Environment |
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Improving Watershed Planning Using Bacterial Source Tracking
2015 SWCS Conference
K. Wagner, G. DiGiovanni, E. Casarez, J. Truesdale, P. Wanjugi, T. Gentry, L. Gregory
Bacteria/Pathogens The #1 Cause of Water Quality Impairment in
Texas
Rank Rivers/Streams Lakes/Reservoirs Bays/Estuaries1 Pathogens (16%) Mercury (43%) Mercury (33%)2 Sediment (12%) Nutrients (18%) PCBs (23%)3 Nutrients (10%) PCBs (16%) Pathogens (21%)
4Organic enrichment /Oxygen Depletion (9%)
Turbidity (8%)Organic enrichment /Oxygen Depletion (17%)
5 PCBs (8%)Organic enrichment /Oxygen Depletion (8%)
Dioxins (14%)
The #1 Cause of River/Stream Impairment in U.S.
Where did the Bacteria (E. coli) Come From?
• Potential sources• Humans
• Domesticated animals
• Wildlife
• Methods for determining sources• Source survey
• Modeling
• Bacterial source tracking (BST)
PREMISE BEHIND BST
Different guts Different
adaptations Different E. coli
strains
Genetic Differences
Phenotypic Differences
Feral
Establishment of Texas BST Program (2007)
• Two DNA fingerprinting methods selected:
• Enterobacterial repetitive intergenic
consensus sequence-polymerase chain
reaction (ERIC-PCR)
• RiboPrinting® (RP)
• Required BST Library Development
Texas E. coli BST Library
• Contains • 1,669 E. coli isolates • From 1,455 different
fecal samples • Representing >50
animal subclasses• Collected from 13
watersheds (& growing) across Texas
Wildlife41%
Domestic Animals
34%
Human25%
Use of Texas E. coli BST Library for Identifying Water Isolates
Isolate
E. coli
DNA
Fingerprint
Compare
to Library
Source ID
Texas E. coli BST Library composition & rates of correct
classification (RCC)Source Class
Number of Isolates
Number of Samples
Library Composition and Expected
Random Rate of Correct
Classification
Calculated Rate of Correct
Classification (RCC)
RCC to Random Ratio***
Left Unidentified
(unique patterns)
HUMAN 364 315 24% 100 4.2 22
DOMESTIC ANIMALS
531 474 35% 100 2.9 19
Pets 86 76 6% 83 13.8 40
Cattle 237 207 16% 93 5.8 11
Avian Livestock 96 83 6% 89 14.8 25
Other Non-Avian Livestock
112 108 7% 90 12.9 14
WILDLIFE 629 569 41% 100 2.4 19
Avian Wildlife 239 221 16% 85 5.3 21
Non-Avian Wildlife
390 348 26% 92 3.5 17
Overall 1524 1358
3-way = 100%
7-way = 92%
20%
Wildlife51%
Human10%Domestic
Animals27%
Unidentified12%
3-Way Split (averages based on findings in 11
watersheds)
Non-Avian Wildlife
32%
Avian Wildlife18%
Pets5%
All Live-stock24%
Human10%
Unidentified12%
5-Way Split(averages based on findings in 10
watersheds)
Non-Avian Wildlife
32%
Avian Wildlife18%
Pets5%
Other Non-Avian Livestock
5%Avian Livestock
5%Cattle13%
Human10%
Unidentified12%
7-Way Split (averages based on findings in 7
watersheds)
Typical landuse in BST watershedsRelation of Landuse to BST ResultsDeveloped vs Pet & Human Contributions
Significant correlation between % of watershed developed and % of isolates from petsNo correlation between % of watershed developed and % of isolates from human
0% 5% 10% 15% 20% 25% 30%-2%0%2%4%6%8%
10%12%14%16%18%
R² = 0.576711679898713
% of watershed developed
% o
f iso
late
s fr
om p
ets
0% 5% 10% 15% 20% 25% 30%0%2%4%6%8%
10%12%14%16%18%
R² = 0.113328300080188
% of watershed developed
% o
f iso
late
s fr
om h
uman
Typical landuse in BST watershedsRelation of Landuse to BST ResultsCattle
No correlation between watershed landuse and % of isolates from cattle
10% 20% 30% 40% 50% 60% 70% 80%0%
5%
10%
15%
20%
25%
R² = 0.404892816738837
% of watershed pasture/range
% o
f iso
late
s ca
ttle
0% 10% 20% 30% 40% 50% 60% 70% 80%0%
5%
10%
15%
20%
25%
R² = 2.38335975988324E-06
% of watershed pasture
% o
f iso
late
s ca
ttle
0% 10% 20% 30% 40% 50% 60% 70% 80%0%
5%
10%
15%
20%
25%
R² = 0.208320974149374
% of watershed range
% o
f iso
late
s ca
ttle
Typical landuse in BST watershedsRelation of Landuse to BST ResultsWildlife
Only one significant correla-tion observed: Btwn % of watershed as pasture/range/forest & % of isolates as non-avian wildlife
80% 82% 84% 86% 88% 90% 92% 94% 96% 98% 100%0%
10%
20%
30%
40%
50%
60%
70%
R² = 0.00673601610141417
% of watershed pasture/forest/range
% o
f iso
late
s w
ildlif
e
80% 82% 84% 86% 88% 90% 92% 94% 96% 98% 100%0%
10%
20%
30%
40%
50%
60%
70%
R² = 0.498558153563506
% of watershed pasture/forest/range
% o
f iso
late
s no
n-av
ian
wild
life
80% 82% 84% 86% 88% 90% 92% 94% 96% 98% 100%0%
10%
20%
30%
40%
50%
60%
70%
R² = 0.207255593935729
% of watershed pasture/forest/range
% o
f iso
late
s av
ian
wild
life
Conclusions
• BST performing well & tremendously helpful in identifying significant bacteria sources
• Wildlife is source of 50% of isolates in predominately rural watersheds
• Generally no correlations between landuse and isolate source (i.e. LULC may not be good predictor of bacteria sources)
Future Methods & Approaches
1. Assess urban watersheds
2. Identify the “Unidentified”– Continue expansion of BST library– Evaluate other sources of E. coli
Future Methods & Approaches
3. Improve Library Independent BST (Bacteroidales)– Genotypic detection of microorganisms based on marker
genes– Does not require known-source library– Rapid & less expensive than library methods
Extract
DNA
PCR amplify
target sequence
Presence/
Absence + + - -
Cycle5 10 15 20 25 30 35 40 45 50 55
Nor
m. F
luor
o.
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0 Threshold
Quantitative
1 2 43
Questions?
• Kevin Wagner• TWRI Assoc. Director• 979-845-2649• [email protected]
• George Di Giovanni• Professor, UT School of
Public Health – El Paso• 915-747-8509• [email protected]
• Terry Gentry• Assoc. Professor, Texas
A&M AgriLife Research• 979-845-5323• [email protected]