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Record W2763929367 · doi:10.24870/cjb.2017-a102

Assessment of antibiotic resistance genes and integrons in commensal Escherichia coli from the Indian urban waste water: Implications and significance for public health

2017· article· en· W2763929367 on OpenAlexvenueno aff
Nambram Somendro Singh, Jugsharan Singh Virdi

Bibliographic record

VenueCanadian Journal of Biotechnology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
Fundersnot available
KeywordsEscherichia coliAntibiotic resistanceGeneMicrobiologyAntibioticsBiologyPublic healthGeneticsBiotechnologyMedicine

Abstract

fetched live from OpenAlex

Antibiotics like β-lactams, quinolones/fluoroquinolones, aminoglycosides and tetracycline constitute the major mainstay of treatment against most infectious diseases including Escherichia coli. Indiscriminate use of antibiotics for human and animal well-being has generated an enormous evolutionary pressure on bacteria especially E.coli, which has a highly plastic/evolving genome. Though, antibiotic resistance (AR) has been extensively studied in pathogenic E.coli, commensal strains have been studied less owing to lesser clinical significance. However, commensal strains pose a serious threat as reservoirs and transmitters of resistance genes to other bacteria. Therefore, the present study was undertaken to investigate the prevalence of resistance genes and integrons in commensal E.coli isolated from river Yamuna, Delhi, India, which receives plentiful urban waste water. Eighty three well-characterized E.coli strains of phylogroups A and B1 isolated from river Yamuna were investigated. Antimicrobial susceptibilities and minimal inhibitory concentrations (MICs) for β-lactams, aminoglycosides, tetracycline and quinolone/fluoroquinolone were determined by disk diffusion and Etest, according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Production of Extended spectrum β-lactamases (ESBL) and AmpC was investigated. Prevalence of antibiotic-resistance genes for β-lactams (blaTEM,blaSHV, blaCTX-M, blaOXA, blaCMY-42), aminoglycosides (rmtA, rmtB, rmtC, armA, str, aacC2), tetracycline (tetA, tetR, tetM, tetW), and plasmid-mediated quinolone resistance, PMQR (qnrA, qnrB, qnrC, qnrD, qnrS, qep, aac) were assessed. Integrons and gene-cassette arrays were characterized. Commensal E.coli strains showed a higher resistance to ampicillin (95%), less to cefazolin (45%) and still lesser to tetracycline (15%). About 19% of these strains showed multidrug resistant (three or more classes of antibiotics), of which 15% also produced ESBLs. None of the strains produced AmpC β-lactamases. About 6% of the strains were concurrently fluoroquinolone-resistant and ESBL producers. The blaTEM was present in most strains (95%), followed by blaCTX-M (15%). Aminoglycoside-resistance genes viz. str and armA were detected in 6% and 8% strains, respectively; tetracycline-resistance genes viz. tetA and tetR in 3% and 6% strains, respectively; and PMQR gene viz. qnrS in 15% of the strains. Class I integron was detected in 64% of the isolates, of which 7 strains had 3 different variable region gene-cassette arrays. dfrA and aadA gene families were widespread among the gene-cassettes identified.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.275
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations2
Published2017
Admission routes1
Has abstractyes

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