Exposure to Al<sub>2</sub>O<sub>3</sub> nanoparticles facilitates conjugative transfer of antibiotic resistance genes from <i>Escherichia coli</i> to <i>Streptomyces</i>
Why this work is in the frame
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Bibliographic record
Abstract
The spread of antibiotic resistance genes (ARGs) has become a global environmental issue; it has been found that nanoparticles (NPs) can promote the transfer of ARGs between bacteria. However, it remains unclear whether NPs can affect this kind of conjugation in Streptomyces, which mainly conjugate with other bacteria via spores. In the present study, we demonstrated that Al2O3 NPs significantly promote the conjugative transfer of ARGs from Escherichia coli (E. coli) ET12567 to Streptomyces coelicolor (S. coelicolor) M145 without the use of heat shock method. The number of transconjugants induced by Al2O3 particles was associated with the size and concentration of Al2O3 particles, exposure time, and the ratio of E. coli and spores. When nanoparticle size was 30 nm at a concentration of 10 mg/L, the conjugation efficiency reached a peak value of 182 cfu/108 spores, which was more than 60-fold higher than that of the control. Compared with nanomaterials, bulk particles exhibited no significant effect on conjugation efficiency. We also explored the mechanisms by which NPs promote conjugative transfer. After the addition of NPs, the intracellular ROS content increased and the expression of the classical porin gene ompC was stimulated. In addition, ROS enhanced the mRNA expression levels of conjugative genes by inhibiting global regulation genes. Meanwhile, expression of the conjugation-related gene intA was also stimulated, ultimately increasing the number of transconjugants. Our results indicated that Al2O3 NPs significantly promoted the conjugative transfer of ARGs from bacteria to spores and aggravated the diffusion of resistance genes in the environment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it