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FECAL SOURCE TRACKING FOR WATER QUALITY

FECAL SOURCE TRACKING FOR WATER QUALITY. C.A. CARSON Food and Agriculture Policy Research Institute Colleges of Agriculture and Veterinary Medicine University Of Missouri. GENERAL APPROACH TO FST/BST.

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FECAL SOURCE TRACKING FOR WATER QUALITY

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  1. FECAL SOURCE TRACKING FOR WATER QUALITY C.A. CARSON Food and Agriculture Policy Research Institute Colleges of Agriculture and Veterinary Medicine University Of Missouri

  2. GENERAL APPROACH TO FST/BST • Routine water sampling shows unacceptable levels of sentinel indicator(s) bacteria indicative of fecal pollution • FST test(s) are chosen to provide evidence of host source(s) • A remediation plan can be developed to decrease pollution for compliance with water quality standards

  3. EPA STANDARDS FOR RECREATIONAL WATERS • Fresh water NMT 200 Fecal coliforms / 100 ml. NMT 126 E. coli / 100 ml. • Salt water NMT 33 Enterococci / 100 ml.

  4. EXAMPLES OF POTENTIAL SOURCES OF FECAL POLLUTION • Human sewage treatment systems - private, collective (aging urban utilities) • CAFO s • Pastured animals • Pet animals • Migratory birds • Wild animals

  5. TARGETING FECAL POLLUTION • Non-pathogenic bacteria-large numbers of harmless bacteria usually present for normal intestinal function • Pathogenic (disease-producing) bacteria-normally absent or in low numbers • Looking for pathogens (the real concern) in water samples resembles “looking for a needle in a haystack” • Finding the haystack is easier • Fecal coliforms; E. coli; Enterococcus are common/plentiful; useful as “indicators”

  6. TIERED CONCERNS • Human vs. nonhuman sources (public health risk) • Identification of human and various nonhuman sources via E. coli or other common indicator organisms

  7. Basis of BST Methods • Particular strains of enteric bacteria (eg. E. coli) inhabit intestinal tracks of humans, animals and birds • These various “host-specific” strains can be distinguished by their different biochemistry (function/phenotype) or different genetic/DNA structure (genotype) • BST can be performed using either of these qualities

  8. FIRST EXAMPLE METHODBacterial Fingerprinting / rep-PCRLibrary-Based Genotyping Procedure • Multiple copies of target repeat elements per E. coli genome • Repeat numbers and locations vary per bacterial strain • Primers amplify segments of DNA between repeats/signature of strain

  9. Cell wall Ribosomes Bacterial chromosomes Cytoplasm Cytoplasmic membrane Flagellum PROKARYOTIC BACTERIAL CELL From: Principles of Microbiology by Atlas. W.C. Brown Co. 2nd Ed. 1997.

  10. rep PCR test – based on location of target gene in E. coli E. coli rep genes DNA chromosome 1 1 2 1 2 3 2 3 3 Human Cow Dog PCR Multiply 1,2,3 PCR Multiply 1,2,3 PCR Multiply 1,2,3 Different DNA Fingerprint patterns

  11. - - - Larger Smaller - + + + + Marker Lane Electrophoresis of Rx mixture with Eth Br Image capture MATERIALS AND METHODS rep PCR PCR BOX A1R primer Lyse cells Select/Grow pure fecal E. coli isolates • Bionumerics software • Similarity coefficients of patterns calculated by dice method with fuzzy logic option. • Discriminant analysis via cross validation of database Pattern analysis by computer program

  12. 10000 5000 3000 2000 1500 1000 800 600 400 FECAL E. coli ISOLATES FROM TWO INDIVIDUAL HUMAN SAMPLES (Bp) (Bp) 10000 5000 3000 2000 1500 1000 800 600 400 200

  13. FECAL E. coli ISOLATES FROM A LITTLE SAC RIVER WATER SAMPLE (Bp) (Bp) 10000 10000 5000 5000 3000 3000 2000 2000 1500 1500 1000 1000 800 800 600 600 400 400 200 200

  14. PATTERN ANALYSIS • DNA fingerprint patterns of fecal E. coli isolates are compiled in known-host database/library (human and non-human hosts) • Environmental (water) E. coli isolates host-associated by comparison with database isolates; maximum similarity with a particular library pattern • Arbitrary cutoff for “unknown” patterns – at least 80% similarity with library pattern; A-C quality factor

  15. SECOND EXAMPLE METHODHost Specific/Gene Specific Targeting Non library-based Procedure • Bacteroides are most numerous human intestinal bacteria • Different hosts have different species and strains • Bacteroides thetaiotaomicron (B. tim) is a human-associated species • PCR test for presence of a B. tim gene in water is used as an indicator of human fecal pollution

  16. Bacteroides thetaiotaomicron Test Target DNA Bacteroides tim Electrophoresis PCR Multiply Target 542 size Human Fecal pollution No Human Feces

  17. Field Application of Bacterial Source Tracking Methods UPPER SHOAL CREEK WATERSHED • 3 county area in extreme SW part of MO; Newton, McDonald, Barry Counties • One of most agriculturally productive areas in MO • 91,000 acres in the watershed; 90% is pasture land grazed by over 300,000 head of cattle and fertilized by spreading poultry litter • 50-80 million poultry produced here yearly • 13 miles of Shoal Creek are designated as impaired due to high fecal coliform (FC) levels

  18. Shoal Creek BST Data

  19. Wildlife 6% Human 25% 27% 11% Wildlife Cattle 45% 19% 11% 21% Cattle Poultry Domestic Animals 17% Human 19% Poultry Domestic Animals Seasonal Fecal E.Coli Sources (Average % Contribution) SUMMER WINTER

  20. 5% Wildlife 7% Human 8% Human 13% 43% 48% 29% 9% Poultry Cattle Cattle Poultry 23% 15% Domestic Animals Domestic Animals Fecal E.Coli Sources and Flow SUMMER STORM FLOWS SUMMER BASE FLOWS Wildlife

  21. STUDY CONCLUSIONS • Cattle (particularly in streams) contribute substantially to water pollution • Waste from pastured animals and spread poultry litter also contribute via runoff to streams • There are multiple host sources of feces that combine for the total contribution • Studies usually reveal multiple host sources, rather than a single host source • Results from routine water quality monitoring, fecal source tracking and visual inspection can all combine to analyze problems and suggest solutions

  22. BOTTOM LINE • BST methods are powerful tools to resolve questions of host sources of fecal pollution and associated high bacterial counts in water • Current consensus is to use a combination of methods with different targets • Results must be interpreted carefully, combined with local observations and based on multiple samples collected over a period of time

  23. ACKNOWLEDGMENT OF TEAM MEMBERS • Food and Agricultural Policy Research Institute • U.S. Environmental Protection Agency • U.S. Geological Survey • College of Agriculture and Natural Resources • Department of Agriculture Engineering • Department of Agriculture Economics • College of Veterinary Medicine • U.S. Department of Agriculture • Missouri Department of Natural Resources • University of Missouri Extension Services

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