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Record W4390666767 · doi:10.3389/fmicb.2023.1292597

Occurrence and characterization of β-lactamase-producing bacteria in biomedical wastewater and in silico enhancement of antibiotic efficacy

2024· article· en· W4390666767 on OpenAlexaff
Sultana Juhara Mannan, Shopnil Akash, Sumaya Afnan Jahin, Ahnaf Tahmid Saqif, Kohinur Begum, Mahmuda Yasmin, Chowdhury Rafiqul Ahsan, Baye Sitotaw, Turki M. Dawoud, Hiba‐Allah Nafidi, Mohammed Bourhia

Bibliographic record

VenueFrontiers in Microbiology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversité Laval
FundersKing Saud University
KeywordsMeropenemAcinetobacter baumanniiEnterobacter cloacaeAntibioticsMicrobiologyIn silicoBiologyAmpicillinBacteriaAntibiotic resistanceAcinetobacterEnterobacterCefuroximePseudomonas aeruginosaEscherichia coliEnterobacteriaceaeGeneGenetics

Abstract

fetched live from OpenAlex

Wastewater discharged from hospitals is a recognized contributor to the dissemination of antibiotic-resistant bacteria and their associated genetic traits into the environment. This study focused on the analysis of β-lactamase-producing pathogenic bacteria within untreated biomedical wastewater originating from various hospitals in Dhaka City, Bangladesh, as well as in silico evaluation and structural activity relationship mentioned antibiotics were evaluated. In silico drug design techniques were applied to identify the relationship with how the functional group impacts the binding energy. Out of the 184 isolates obtained from well-established hospital sewage discharge points in Dhaka, 89 were identified as β-lactamase positive. These bacteria were subjected to antimicrobial susceptibility testing using the VITEK-2 assay, and their profiles of extended-spectrum beta-lactamase (ESBL) production were determined through molecular methodologies. Among the β-lactamase-positive isolates, considerable resistance was observed, particularly against ampicillin, Ceftriaxone, Cefuroxime, and Meropenem. The predominant resistant species included Escherichia coli, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter cloacae. The study identified the prevalence of ESBL-producing genes, with blaNDM-1 being the most prevalent, followed by blaOXA-1, blaSHV, blaCTX-M, and blaKPC. None of the isolates carried the blaTEM gene. In addition to characterizing these bacteria, the research explored ways to enhance the binding energy of four existing antibiotics as new inhibitors through computational studies. The findings revealed significant improvements in binding energy. Specifically, Meropenem initially exhibited a binding energy of −7.5 kcal/mol, notably increasing to −8.3 kcal/mol after modification. With an initial binding energy was only −7.9 kcal/mol, Ampicillin experienced an enhancement, reaching −8.0 kcal/mol post-modification. Similarly, Ceftriaxone, with an initial binding energy of −8.2 kcal/mol, increased to −8.5 kcal/mol following structural adjustments. Finally, Cefuroxime, initially registering a binding energy of −7.1 kcal/mol, substantially increased to −8.9 kcal/mol after modification. This finding establishes a foundation for future investigations in the development of modified antibiotics to address the issue of antibiotic resistance. It presents prospective remedies for the persistent problem of antibiotic-resistant bacteria in healthcare and the environment.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.228
Teacher spread0.222 · 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 designBench or experimental
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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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