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Environmental Microbiology

Comparison of Gull Feces-Specific Assays Targeting the 16S rRNA Genes of Catellicoccus marimammalium and Streptococcus spp.

Hodon Ryu, John F. Griffith, Izhar U. H. Khan, Stephen Hill, Thomas A. Edge, Carlos Toledo-Hernandez, Joel Gonzalez-Nieves, Jorge Santo Domingo
Hodon Ryu
aNational Risk Management Research Laboratory, Cincinnati, Ohio, USA
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John F. Griffith
bSouthern California Coastal Water Research Project, Costa Mesa, California, USA
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Izhar U. H. Khan
cNational Water Research Institute, Environment Canada, Burlington, Ontario, Canada
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Stephen Hill
cNational Water Research Institute, Environment Canada, Burlington, Ontario, Canada
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Thomas A. Edge
cNational Water Research Institute, Environment Canada, Burlington, Ontario, Canada
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Carlos Toledo-Hernandez
dDepartment of Biology, University of Puerto Rico, San Juan, Puerto Rico
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Joel Gonzalez-Nieves
dDepartment of Biology, University of Puerto Rico, San Juan, Puerto Rico
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Jorge Santo Domingo
aNational Risk Management Research Laboratory, Cincinnati, Ohio, USA
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DOI: 10.1128/AEM.07192-11
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  • Fig 1
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    Fig 1

    Venn diagram for gull-specific assay positives against gull feces (top) and water impacted with gull fecal contamination (bottom). Numbers outside the circles represent numbers of samples that tested negative with all assays.

  • Fig 2
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    Fig 2

    Mean copy numbers of target markers in gull fecal DNA in samples positive and negative with the gull3 assay. To calculate mean concentrations, below detection limits were treated as zero, and double-peak values from the gull2 assay were not considered. Error bars represent one standard deviation.

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    Fig 3

    Mean copy numbers of markers in fecal DNA extracts. To calculate mean concentrations, the below detection limit values were treated as zero, and double-peak values from the gull2 assay were not considered. Error bars represent one standard deviation. The gull2 marker was not detected in any of crane and snow goose fecal samples.

  • Fig 4
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    Fig 4

    Probability of gull fecal contamination using a Bayesian statistical model. (A) Posterior probability of contamination given a positive qPCR result using three different gull-specific assays over a range of prior probabilities; (B) posterior probability of contamination given a negative qPCR result using three different gull-specific assays over a range of prior probabilities.

Tables

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  • Table 1

    Summary of oligonucleotide primers and probes for gull-specific qPCR assays

    AssayPrimer/probe sequence (5′ to 3′)Ta (°C)aSize (bp)Reference or source
    gull2 SYBR greenForward: TGCATCGACCTAAAGTTTTGAG6441224
    Reverse: GTCAAAGAGCGAGCAGTTACTA6441224
    gull3 SYBR greenSAG1F: ATTTAACCCATGTTAGATGC56319This study
    SAG1R: CGTCCCTTTCTGGTAAGT56319This study
    gull4 TaqManqGull7F: CTTGCATCGACCTAAAGTTTTGAG60116This study
    qGull8R: GGTTCTCTGTATTATGCGGTATTAGCA60116This study
    qGull7Pb: FAM-ACACGTGGGTAACCTGCCCATCAGA-TAMRA60116This study
    • ↵a Optimum PCR annealing temperatures were determined using temperature gradients.

    • ↵b FAM, 6-carboxyfluorescein, fluorescence reporter dye; TAMRA, 6-carboxytetramethylrhodamine, fluorescence quencher dye.

  • Table 2

    Distribution of 16S rRNA genes in the clone library of gull feces

    Class or group% clones of totalGenusNo. of clonesa
    This study (n = 354)Lu et al. (n = 282)This studyLu et al.
    Fusobacteria3.10.7Cetobacterium112
    Bacilli69.237.2Bacillus03
    Weissella50
    Lactobacillus69
    Streptococcus1160
    Catellicoccus6874
    Unclassified Lactobacillales507
    Clostridia3.117.3Dialister10
    Subdoligranulum30
    Clostridium344
    Unknown22
    Erysipelotrichi0.90Turicibacter1–
    Unknown2
    Alphaproteobacteria0.36.7Rubellimicrobium10
    Paracoccus08
    Betaproteobacteria04.3Acidovorax–6
    Epsilonproteobacteria0.30.4Campylobacter11
    Gammaproteobacteria16.711.3Acinetobacter013
    Enterobacter16
    Escherichia06
    Citrobacter30
    Shigella60
    Klebsiella175
    Unknown320
    Sphingobacteria0.60Unknown2–
    Actinobacteria0.66.4Corynebacterium08
    Unknown23
    Mollicutes0.30Ureaplasma1–
    Bacteroidetes01.1Bacteroides–1
    Unknown5.13.2Unknown189
    • ↵a –, not found.

  • Table 3

    Prevalence of gull markers in various animal feces

    Animal typeAnimalLocation of samplesNo. of samplesNo. of positive samples
    SYBR greenTaqMan, gull4
    gull2gull3
    GullCalifornia gull (Larus californicus)California15913844143
    Ring-billed gull (L. delawarensis)Ohio2222
    Glaucous-winged gull (L. glaucescens)Alaska6453250
    Laughing gull (L. atricilla)Georgia5522
    Laughing gull (L. atricilla)Delaware3233
    Herring gull (L. smithsonianus)Delaware20161618
    Gray headed gull (L. cirrocephalus)South Africa2222
    Total25521871221
    Poultry and waterfowlChicken (houses)Puerto Rico9812238
    TurkeyPuerto Rico5050
    DuckPuerto Rico160160
    PigeonPuerto Rico11122
    HeronPuerto Rico1000
    SwanPuerto Rico22090
    GuineafowlPuerto Rico11010
    CraneNebraska12028
    Snow geeseNebraska10004
    PelicanCalifornia10101010
    Red KnotDelaware17101
    TurnstoneDelaware5211
    Canada geeseAlaska25604
    MallardAlaska6010
    Total249327638
    Nonavian speciesCattlePuerto Rico66050
    GoatPuerto Rico32050
    MonkeyPuerto Rico9000
    FishPuerto Rico13100
    HorsePuerto Rico30130
    PigPuerto Rico308131
    Total18010271
  • Table 4

    Detection of gull markers in water samples by gull-specific assays

    Sampling location(s)Sample typeSampling periodNo. of water samplesNo. of samples positive with:Presumed primary fecal contamination sourcea
    gull2gull3gull4
    California beachFreshwater and seawaterMay to September 2008338293202312Gull
    Delaware beachFreshwater and seawaterMay 20116546Gull
    Anchorage, AKFreshwaterOctober 20105111Gull
    Anchorage, AKFreshwaterOctober 20103000Unknown
    Toronto, CanadaWater treatment plant intake (Lake Ontario offshore)December 20099000Unknown
    Toronto, CanadaSewage treatment plant effluentDecember 20093000Human, gull
    Toronto, CanadaSewage treatment plant effluent and CSO samplesbDecember 20096000Human
    Sumas watershed, BC, Canada (agriculture-impacted sites)FreshwaterApril 2007 to December 200764122610Chicken, some livestock
    Sumas Watershed, BC, Canada (reference site)FreshwaterApril 2007 to December 200716152Wildlife
    Puerto RicoFreshwaterSeptember 2010 to January 20111380190Domesticated animals (including chicken)
    • ↵a There is historical knowledge that host animals are present at these sites a significant part of the year.

    • ↵b CSO, combined sewer overflow.

  • Table 5

    Bayesian statistics for the three qPCR assays against gull-impacted water samplesa

    AssayConditional probabilitySensitivitySpecificityPrevailing rate
    gull20.980.850.900.86
    gull30.630.280.760.59
    gull40.990.870.910.91
    • ↵a The conditional probability [i.e., posterior probability or P(A|B) in the Bayesian formula] was calculated using a Bayesian statistical model. The sensitivity is the ratio of positive signals in gull fecal samples. It is numerically identical to P(B|A) in the Bayesian formula. The specificity is the ratio of negative signals in nongull fecal samples. It is numerically identical to 1 − P(B|A′) in the Bayesian formula. The prevailing rate is the ratio of positive signals in water samples. It is numerically identical to P(A) in the Bayesian formula.

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Comparison of Gull Feces-Specific Assays Targeting the 16S rRNA Genes of Catellicoccus marimammalium and Streptococcus spp.
Hodon Ryu, John F. Griffith, Izhar U. H. Khan, Stephen Hill, Thomas A. Edge, Carlos Toledo-Hernandez, Joel Gonzalez-Nieves, Jorge Santo Domingo
Applied and Environmental Microbiology Feb 2012, 78 (6) 1909-1916; DOI: 10.1128/AEM.07192-11

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Comparison of Gull Feces-Specific Assays Targeting the 16S rRNA Genes of Catellicoccus marimammalium and Streptococcus spp.
Hodon Ryu, John F. Griffith, Izhar U. H. Khan, Stephen Hill, Thomas A. Edge, Carlos Toledo-Hernandez, Joel Gonzalez-Nieves, Jorge Santo Domingo
Applied and Environmental Microbiology Feb 2012, 78 (6) 1909-1916; DOI: 10.1128/AEM.07192-11
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