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Profiling Virulence and Antimicrobial Resistance Markers of Enterovirulent Escherichia Coli from Fecal Isolates of Adult Patients with Enteric Infections in West Cameroon.
- Source :
- Osong Public Health & Research Perspectives; Aug2020, Vol. 11 Issue 4, p216-230, 15p
- Publication Year :
- 2020
-
Abstract
- Objectives: This study aimed to identify virulent and antimicrobial resistant genes in fecal E. coli in Mbouda, Cameroon. Methods: A total of 599 fecal samples were collected from patients with enteric infections who were = 20 years old. E. coli was isolated on the MacConkey agar and virulent genes were detected by multiplex/simplex PCR. Isolates in which = 1 virulent gene was detected were subjected to antibiotic susceptibility testing. The resulting resistant isolates were subjected to PCR, followed by sequencing for resistant genes detection. Results: There were 119 enterovirulent E. coli identified, amongst which 47.05% were atypical enteropathogenic E. coli (EPEC), 36.97% enterotoxigenic E. coli, 10.08% Shiga toxin producing E. coli (STEC) and 5.88% were enteroinvasive E. coli (EIEC). The occurrence of the eae gene (47.06%) was higher compared with CVD432 (33.61%), aaic (13.45%), stx2 (10.08%) and stx1 (0.84%). High resistance rates were noted for ampicillin (94.64% EPEC, 91.67% STEC, 59.09% EAEC, and 57.14% EIEC) and sulfamethoxazoletrimethoprim (100% EPEC and 83.33% STEC, 81.82% EAEC and 71.43% EIEC). sul2 (71.43%), tetB (64.71%), tetA (59.94%) and blaTEM (52.10%) were detected. A double mutation (S83L; D87N) was seen in gyrA and a single mutation (S80I) was observed in parC. Conclusion: These findings suggested that measures should be taken to reduce the harm of E. coli to public health. [ABSTRACT FROM AUTHOR]
- Subjects :
- DNA analysis
FECAL analysis
BACTERIAL protein analysis
CHI-squared test
CHLORAMPHENICOL
CO-trimoxazole
DIARRHEA
DRUG resistance in microorganisms
ESCHERICHIA coli
ESCHERICHIA coli diseases
MULTIDRUG resistance
GENETIC mutation
POLYMERASE chain reaction
TETRACYCLINE
MICROBIAL virulence
AMPICILLIN
DATA analysis software
DESCRIPTIVE statistics
Subjects
Details
- Language :
- English
- ISSN :
- 22109099
- Volume :
- 11
- Issue :
- 4
- Database :
- Supplemental Index
- Journal :
- Osong Public Health & Research Perspectives
- Publication Type :
- Academic Journal
- Accession number :
- 145332139
- Full Text :
- https://doi.org/10.24171/j.phrp.2020.11.4.11