Environmental concentrations of antibiotics, biocides, and heavy metals fail to induce phenotypic antimicrobial resistance in Escherichia coli
Bibliographic record
Abstract
Most anthropogenically affected environments contain mixtures of pollutants from different sources. The impact of these pollutants is usually the combined effect of the individual polluting constituents. However, how these stressors contribute to the development of antimicrobial resistance in environmental microorganisms is poorly understood. Thus, a 30-day exposure experiment to environmental and sub-inhibitory concentrations of oxytetracycline, amoxicillin, zinc, copper, BAC (benzalkonium chloride) 10 and DADMAC (diallyldimethylammonium chloride) 12, was conducted using fully susceptible E. coli ATCC 25922 to ascertain any development of phenotypic or genotypic resistance. Furthermore, wild-type isolates were collected from the same aquatic environment as the stressors, analysed for phenotypic resistance using the disk diffusion method and genotypically through whole genome sequencing. Exposure to the various concentrations and combinations of the stressors did not trigger phenotypic resistance in the experimental bacteria. Furthermore, genotypic analysis of the WGS on the exposed isolates only found the macrolide resistance mdf(A) gene (also present in the control strain) and the disinfectant resistance gene sitABCD. With further analysis for single nucleotide variants (SNV), mutations were detected for 19 genes that encoded for oxidative stress, DNA repair, membrane proteins efflux systems, growth and persister formations except for the robA, a transcription protein subset of the ArcC/XylS family of proteins, which confer multidrug resistance in E. coli. This indicates that exposure to sub-inhibitory concentrations of antibiotics, heavy metals and biocide residues in the aquatic environmental concentrations of the stressors identified in the current study could not induce phenotypic or genotypic resistance but encoded for genes responsible for the development of persistence and tolerance in bacteria, which could be a precursor to the development of resistance in environmental bacteria.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".