Developing a Multiplex PCR Platform to Determine the Virulence Genes of Escherichia Coli in Boulevard Lake, Thunder Bay, Ontario
Notice bibliographique
Résumé
Given the evidence that E. coli can establish in the periphytic community and be released back into the water column, it is important to understand the pathogenicity of this group of E. coli by examining the virulence genes that they possess. In this study, an optimized DNA extraction method and multiplex PCR platform were developed to detect the virulence genes of five major pathotypes of E. coli (enteropathogenic E. coli, ETEC; enteropathogenic E. coli, EPEC; shiga toxin-producing E. coli, STEC; enteroinvasive E. coli, EIEC; and uropathogenic E. coli, UPEC). The multiplex PCR platform was used to examine the virulence genes of E. coli isolates from the periphyton and lakewater samples from Boulevard Lake, Thunder Bay, Ontario. In addition, E. coli isolated from goose feces and sewer pumping stations around the lake were also tested. \nFour DNA extraction methods were compared including the: (I) Fermentas Genomic DNA Extraction Kit, (II) XS Buffer method, (III) Chelex DNA extraction method, and (IV) Chelex+RNase method. The average amounts of DNA obtained by the four methods were 1.1, 14.9, 140.7 and 150.2 ?g/109 cells, respectively. However, only the DNAs extracted by the XS Buffer method were able to be specifically amplified by their respective PCR primers. Therefore, the XS Buffer method was selected in this study. \nThree sets of multiplex PCR primers were initially designed to target and amplify nine specific virulence genes of the five major pathotypes of E. coli. Since the multiplex primers Set 2 and 3 were not functioning properly, they were replaced by multiplex PCR primers Set 4 and 5, respectively. The Set 1 primers contained the hs and hl primers that amplified the heat-stable enterotoxin (hs) and heat-labile enterotoxin (hl) genes of ETEC respectively, and ironEC primers for the iron sequestering gene (ironEC) of UPEC. The Set 1 multiplex primers successfully amplified the target genes either individually or simultaneously to produce specific DNA fragments at 170, 322 and 665 bp respectively. The Set 4 multiplex primers amplified the ial of EIEC, bfpA of EPEC and hly of UPEC to produce amplicons of 650, 324 and 1000 bp respectively. Finally, the Set 5 multiplex primers amplified the shiga-like toxin I and II genes (stxI and stxII) of STEC and papA of UPEC successfully to produce amplicons of 150, 255 and 720 bp respectively. \nThe multiplex primers Set 1, 4 and 5 were used to determine the presence of the nine targeted virulence genes in 306 E. coli isolates isolated from the periphyton, lakewater, goose feces and sewage samples in or around Boulevard Lake. The percentage of E. coli isolates in the sewage (37 isolates), goose (38 isolates), periphyton (75 isolates) and lakewater (76 and 80 isolates collected in 2010 and 2014 respectively) samples that contained one or more virulence gene(s) were 48.5, 28.9, 2.6, 5.3 and 5.0 % respectively. The results indicate that the periphytons were likely to be the major source of E. coli in Boulevard Lake. Furthermore, with the exception of two potential diarrheagenic E. coli isolates from the sewage (with hl gene) and 2014 lakewater (with bfpA gene) samples, all the virulence gene-positive isolates belonged to the uropathogenic E. coli pathotype.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».