Source Tracking Studies in the New York City Watershed

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2 Source Tracking Studies in the New York City Watershed (The ever changing Microbial Toolbox!) Kerri A. Alderisio NYC DEP Bureau of Water Supply Division of Drinking Water Quality Control

3 Outline Introduction to the NYC Water Supply Research Microbiology Unit mission Methods Case studies Coliphage typing Ribotyping Genotyping Summary

4 NYC System Statistics 1,972 square-mile watershed 19 reservoirs, 3 controlled lakes 1.2 BGD, 9 million people Catskill and Delaware 90% Croton 10% Varying land uses

5 The NYC Water Supply

6 Research Microbiology Unit Mission: To compliment routine microbiology operations by investigating unusual microbiological occurrences in the NYC watershed. May include investigation of algal or bacterial blooms, bacterial source identification, protozoan analysis, and any contamination of the system through accidental or intentional actions.

7 Why?

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10 Methods Serotyping E. coli Electrophoretic typing E. coli Fecal Streptococcus/ Enterococcus Clostridium perfringens Coliphage typing Ribotyping E. coli Cryptosporidium genotyping

11 How do they work? F-specific RNA coliphage analysis subtyping for group characterization Ribotyping E. coli comparing to a library of sources Genotyping Cryptosporidium oocysts Subspeciating and comparing genetic patterns

12 Correlation of fecal coliforms and F-specific RNA coliphages

13 Plaque growth

14 F-specific RNA Coliphage Groups Group I almost exclusively non-human animals Group II predominantly human source, (bovine, swine) Group III predominantly human and swine sources Group IV predominantly non-human sources

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16 Coliphage Results Summary Kensico Reservoir Study Group Site 4 N5 Cove Woodman s Cove I 107/115 64/73 6/19 (93%) (88%) (32%) II III 1/ (0.9%) IV 0 0 0

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18 Fecal Coliform Concentrations of Local Gulls and Geese 249 Ring-Billed Gulls Gull feces = 3.68 x 10E8 FC per gram Gull feces weight = 0.48g 236 Canada Geese Goose feces = 1.53 x 10E4 FC per gram Goose feces weight = 8.35g

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20 Kensico Reservoir Waterbirds Waterfowl Program Data BIRD SURVEYS BEGAN HERE WATERBIRD MANAGEMENT Number of Waterbirds Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03

21 % of Samples >20 CFU in last 6 Months 50% 40% 30% 20% 10% 0% Kensico Reservoir Keypoints Fecal Coliform Bacteria Kensico Laboratory Data BYPASS SWTR COMPLIANCE LIMIT CATLEFF DEL 18 WATERFOWL HAZING Jan-87 Jan-88 Jan-89 Jan-90 Jan-91 Jan-92 Jan-93 Jan-94 Jan-95 Jan-96 Jan-97 Jan-98 Jan-99 Jan-00 Jan-01 Jan-02 Jan-03

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23 Ribotyping Creating a library of E.coli sources: Are all libraries created equally? Is there geographic diversity among species? What about transient and resident strains? What about the consumption cycle? Does E. coli have what it takes? Promising for the future

24 E. coli from Goose Feces and an Effluent Chamber Using EcoR1 and HIND III

25 Objectives of the Cryptosporidium Genotyping Study To capture oocysts from storm samples and recover them in the laboratory for molecular analysis To identify the sources of Cryptosporidium in two sub-basins thorough the use of molecular techniques To assess the human-infective potential of Cryptosporidium spp. found in storm water in two watersheds (Ashokan and Malcolm Brooks) of NYC DEP

26 Importance of Molecular Tools in the Study of Cryptosporidium in Water Useful in the assessment of human infection potential of Cryptosporidium parasites found in water Only a few Cryptosporidium spp. are human pathogens Among human-pathogenic Cryptosporidium spp., the public health significance of different species is different Helpful to the identification of contamination sources Most Cryptosporidium spp. preferentially infect specific hosts

27 Similarity in Immunofluorescence of Oocysts from Human-pathogenic and Non-human-pathogenic Cryptosporidium spp. C. hominis C. parvum bovine C. parvum mouse C. saurophilum C. muris C. baileyi

28 Human-pathogenic Cryptosporidium spp. C. hominis C. parvum C. meleagridis C. felis C. canis C. muris Cryptosporidium cervine genotype C. suis

29 Methodology Collection of storm water samples by ISCO6700 autosampler Sample processing by ICR method or method 1623 Sample processing by IMS and DNA extraction Microscopy and oocyst enumeration PCR, RFLP, DNA sequencing

30 Differences in the Ecology between Ashokan and Malcolm Brooks, NYCDEP Ashokan Brook Malcolm Brook Forest Grass/lawn Impervious Water Wetland Ashokan 78% 8% 6% 1% 7% Malcolm 31% 31% 32% <1% <6%

31 Differentiation of Cryptosporidium Species and Genotypes by SSU rrna-based PCR-RFLP 1, , bp C. muris 2. C. serpentis 3. C. baileyi 4. C. felis 5. C. meleagridis 6. C. wrairi 7. pig genotype I 8. C. canis 9. C. saurophilum 10. ferret genotype 11. marsupial genotype I 12. mouse genotype 13. C. parvum 14. C. hominis Upper panel: SspI digestion Lower panel: VspI digestion Based on Xiao et al., 1999a, 1999b

32 Ashokan Brook Malcolm Brook W8 W7 W1 W5 W11 W3 W substitutions/site H2O H2O741 H2O H2O H2O H2O H2O H2O1372 H2O H H2O H2O H2O H2O H2O742 H2O744 H2O H2O H2O H2O745 H2O H2O H2O H2O H2O H2O743Q-12 H2O H2O H2O H2O743 H20594p H2O H2O H2O1371 H2O H2O H2O960Q-33 H2O H2O H2O W2 W6 W10 W substitutions/site a N b8 N N N N6016a a r r N N N a N6017a d-2 N p r r N r6012a-3 r r b6 6013b N6019b N6013a-29 r6012b-7 N6018a-39 N6012a b5 N6013b a a9 r b N N r a N6014b-33 N r a a10 r6016a a-1 r N r6018a-12 N r r W14 W 7 W15 W17 W1 W13 W5 W11 W3 W4 W16 W18? Sources of Cryptosporidium Contamination in Storm Water from Ashokan and Malcolm Brooks, NYCDEP

33 Number of Genotypes per Storm Water Sample from the Malcolm and Ashokan Brooks No. of genotypes by sample No of samples (%) Ashokan Malcolm Brook Brook 2 (6.9) 8 (20.0) 16 (55.2) 12 (30.0) 9 (31.0) 10 (25.0) 2 (6.9) 8 (20.0) 0 1 (2.5) 0 1 (2.5)

34 Distribution of Cryptosporidium genotypes in storm water from Ashokan and Malcolm Brooks in New York 40% Ashokan brook Malcolm brook 30% 26% 20% 10% 0% 10% 12% 8% 0% 5% 4% 20% 3% 4% 10% 0% 18% 14% 0% 5% 3% 0% 0% 8% 10% 7% 3% 0% 0% 7% 0% 9% 0% 8% 0% 4% 0% 4% 0% 1% w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 w15 w16 w17 w18

35 Summary There is no single source tracking analysis that points to the smoking gun All source tracking strongly suggests predominantly non-human influence in NYC watershed so far Need more work on sources for RT, and positive controls for human influences Any Questions?