molecular indicators used in the development of predictive

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.

molecular indicators used in the development of predictive

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