Genetic characterization of extended-spectrum β-Lactamase- and carbapenemase-producing Escherichia coli isolated from Egyptian hospitals and environments
Bibliographic record
Abstract
Over the past decades, Escherichia coli (E. coli) have acquired extensive resistance to antibiotics; especially β- lactams. This study aimed to investigate the frequency of Extended-spectrum β-lactamase (ESBL) and carbapenemase producers among E. coli isolates and their correlation with serotypes, phylogenetic background, and pathogenicity associated islands. A total of 105 E. coli strains were isolated and subjected to antimicrobial susceptibility testing against β-lactam antibiotics. All isolates showed a high resistance profile. Resistant isolates were tested for ESBL and carbapenemase production. Fifty-three and 18 isolates were positive for ESBL and carbapenemase producers, respectively. ESBL and carbapenemase genes were detected by PCR. TEM gene was the most prevalent gene among all isolates followed by SHV and CTX-M15. In carbapenemase-producers, OXA-48 and IMP were the predominant genes. Enteropathogenic E. coli (EPEC) and Enterohemorrhagic E. coli (EHEC) were the major producers of ESBL and carbapenemase, respectively as indicated by serodiagnosis. They were further assessed for the presence of pathogenicity islands (PAIs) and phylogenetic background. The most predominant DEC PAI and ExPEC PAI were HPI and IICFT073. Most clinically ESBL-producers were group D and B2 while environmentally ones were group B1 and A. On contrary, clinically carbapenemase-producers belonged to group C and D. In conclusion, our study confirms the importance of phylogenetic group D, B2, and C origin for antibiotic resistance in E. coli. Ultimately, our findings support the fact that environmental isolates contribute to the local spread of E. coli pathogenicity in Egypt and these isolates maybe serve as reservoirs for transmission of resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".