Plasmid transmitted small multidrug resistant (SMR) efflux pumps differ in gene regulation and enhance tolerance to quaternary ammonium compounds (QAC) when grown as biofilms
Bibliographic record
Abstract
Abstract Small multidrug resistance (SMR) efflux pump genes are commonly identified from integrons carried by multidrug-resistant (MDR) plasmids. SMR pumps are annotated as ‘ qac ’ for their ability to confer resistance to quaternary ammonium compounds (QACs) but few qac are characterized to date. Hence, we have examined SMR sequence diversity, antimicrobial susceptibility, and gene expression from >500 sequenced proteobacterial plasmids. SMR sequence diversity from plasmid database surveys identified 20 unique SMR sequences annotated as qacE/EΔ1/F/G/H/I/L , or sugE . Phylogenetic analysis shows ‘Qac’ sequences are homologous to archetypical SMR member EmrE, and share a single sequence origin. In contrast, SugE sequences are homologous to archetypical member Gdx/SugE and likely originate from different species. SMR genes, qacE, qacEΔ1, qacF, qacG, qacH , and sugE(p) , were over-expressed in Escherichia coli to determine their QAC antimicrobial susceptibility as planktonic, colony, and biofilms. SMRs (except qacEΔ1/sugE ) expressed in biofilms significantly increased its QAC tolerance as compared to planktonic and colony growth. Analysis of upstream SMR nucleotide regions indicate sugE(p) genes are regulated by type II guanidinium riboswitches, whereas qacE and qacEΔ1 have a conserved class I integron Pq promoter, and qacF/G/H are regulated by integron Pc promoter in variable cassettes region. Beta-galactosidase assays were used to characterize growth conditions regulating Pq and Pc promoters and revealed that Pq and Pc have different expression profiles during heat, peroxide, and QAC exposure. Altogether, this study reveals that biofilm growth methods are optimal for SMR-mediated QAC susceptibility testing and suggests SMR gene regulation on plasmids is similar to chromosomally inherited SMR members.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".