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8/6/2019 Molecular Indicators Used in the Development of Predictive
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Molecular Indicators Used in the
Development of Predictive Modelsfor Microbial Source Tracking
Aisha Akram
Roll # 20
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INTRODUCTION
Fecal pollution r epresents serious health
problems associated with the pathogens from
the infected animals and humans. Fecal coliforms indicate the presence of fecal
matter but does not identify the source of fecal
contamination.
A number of chemical, microbial, and
eukaryotic indicators have been proposed as
indicators of f ecal pollution sources in water
bodies.
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Microbial source tracking (MST)provide rapid
fecal sour ce determination and facilitate
remediation.o Several Bifidobacterium species are human
specific such as Bifidobacterium adolescentis
and Bifidobacterium dentium and the
molecular markers used for their identification
are (ADO)and(DEN) respectively.
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o Bacteriodetes markers ar e based on host-specific oligonucleotide i.e.HF-134 andHF183F for human Bacteriodetes and CF128F
and CF193F for ruminant Bacteriodetes.
o The gene esp. ofEnterococcus which encodes
an enterococcal surface protein has also beenproposed as an indicator of human f ecalpollution.
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o OtherMST eukaryotic markers used were host
specific mitochondrial DNA associated with
humans, cattle and pigs (Humito,Bomito andPomito respectively).
Predictive models to distinguish between
human and non human f ecal pollution have
been developedby combining indicators.
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MATERIALSANDMETHODS
Sample collection
144 samples ofwastewater, feces and slurry
were collected from human and animal source.DNA extraction
Genomic DNA from 200 l of the sample was
extracted using Q1A amp DNA blood extraction
minikit.
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Bacteriodetes group detection
Specific primers were used to discriminate
bacteriodetes from human and ruminant sources
of fecal pollution.
Human HF134F, HF183F
Ruminants CF128F,CF193F
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The 30 cyclePCR reaction was performed in
Perkin Elmer thermocycler.
Initial denaturation 94C for 2 min
Denaturation 94C for 1 min
Annealing temperature 62C - 63C for 1 min
Extraction 72C for 1.5 minFinal 7-min extension at 72C .
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Detection of gene esp. ofE.faecium
The method fordetecting the geneesp requires
a previous cultivation stage
Samples were first processed by 0.45-m
porous membrane filters
Filters were incubated on m-Enterococcus agar
and incubated for 48 h at 37C
Filters were suspended on tryptic soy broth and
incubated for 3 h at 41C. Then, DNAextraction was performed using a QIAamp
DNA blood minikit
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The genewas amplified using a forwardprimerthat is specific for the protein esp.
Mitochondrial DNA
Nested-PCR assays were performed on eachsample to detect mitochondrial host-specific DNAassociatedwith humans, cattle, and pigs
Statistical analysis
Sensitivity (r) and specificity (s)were
calculated according to the following formulas:
r= [TP/(TP+FN)]
s = [TN/(TN+FP)]
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Where,
TPis the number of samples that were positive forthePCR marker of their own species (true
positive)
FNis the number of samples that were negative
for a PCR marker of their own species (falsenegative)
TNis the number of samples that were negative
for a PCR marker of another species (truenegative)
FPis the number of samples that were positive for
a PCR marker of another species (false positive).
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Predictive models
Linear and quadraticdiscriminant analysis(LDA and QDA) arewidely used
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RESULTS
Assay validation
The sensitivity and specificity of the markers
were tested against DNA extracted from host-specific samples.
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Comparisons between the positive samples for
each marker are shown in Table 1
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The values obtained for the sensitivity,
specificity, and conditional probability of each
marker are shown in Table 2.
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ADO ------95.6% human samples positive
DEN ------ 64.4% human samples positive HF134 ------ 30% humanBacteroidetes marker
HF183 ------ 50% humanBacteroidetes marker
CF128 ------ 26% ruminantBacteroidetesmarker
esp gene ------ 77% sensitivity for human
esp gene ------ 68% sensitivity forcows andpigs
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Three mitochondrial DNA markers
Humito -------- 84.4% sensitivity for human Bomito -------- 84.2% sensitivity for bovine
Pomito -------- 87.9% sensitivity for porcine
Predictive models Several models were developed to distinguish
between the four possible fecal pollution
sources (labeled HPBP: human, porcine,bovine, poultry) (Table 3).
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Models fordiscriminating human and
nonhuman sources (labeled H-NH) are alsoshown in Table 3.
The predictive model for HPBP
seven markers (HF134, HF183, ADO, DEN,
Humito, Bomito, andPomito)
Correctly classified 79.5% sample source.
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Other methods used less number of markers
Decision tree models correctly classified:
DTa 4 mark ers (ADO, HF183, Bomito,
and Pomito)
71.3%
DTb 3mark ers (ADO, Bomito, andPomito)
75.7%
DTa 3 mark ers (ADO, HF183, and
Pomito)
87.5%
DTa 4 mark ers (ADO, DEN, HF134, and
Humito )
89.7%
DTb 2 mark ers (ADO and Pomito) 84.6
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DISCUSSION
B. adolescentis has been reported as one of the
most abundant species ofBifidobacterium in
the human microbiota.B. dentium is less
abundant, but is also described in the
composition of normal human microbiota.
Therefore, both species havebeen described as
possible markers of fecal human pollution intheenvironment .Thedetection of both species
by an ADO-DEN multiplexPCR
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ADO had the highest sensitivity and DEN hadthe highest specificity.
Bacteroidetes markers have been used in manydifferent locations around theworld to identifythe source of the fecal pollution.
Theesp marker is related to human pathogenicstrains ofE. faecium.
The method fordetecting theesp gene requiresan enrichment step beforePCR.Without thisstep, the technique is not sensitiveenough todetect the potential marker.
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Large amounts ofexfoliated epithelial cells are
removedwith feces. Every cell has a high
number of mitochondria, andevery
mitochondrion has many copies of
mitochondrial DNA.
The use of nestedPCR increases the sensitivity
of the technique.
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The percentage ofcorrect identification
increasedwith the number of markers
analyzed.
The best predictive model fordistinguishing
human from nonhuman fecal sources was
based on 5 molecular markers (HF134, ADO,
DEN, Bomito, andPomito) and provided90.1% correct classification.
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CONCLUSION
Some molecular markers could beconsidered
potentialMST indicators.
They could be used as new parameters incombination with otherculture-dependent
MST indicators (host specific or unspecific)
for thedevelopment of feasible universal
predictive models in order to determine fecalpollution sources in water bodies.
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