Functional and genetic characterization of an <i>incF</i> -type multidrug resistance plasmid isolated from fresh spinach
Bibliographic record
Abstract
Abstract The presence of antibiotic-resistant bacteria and clinically-relevant antibiotic resistance genes within raw foods is an on-going food safety concern. It is particularly important to be aware of the microbial quality of fresh produce because foods such as leafy greens including lettuce and spinach are minimally processed and often consumed raw therefore they often lack a microbial inactivation step. This study characterizes the genetic and functional aspects of a mobile, multidrug resistance plasmid, pLGP4, isolated from fresh spinach bought from a farmers’ market. pLGP4 was isolated using a bacterial conjugation approach. The functional characteristics of the plasmid were determined using multidrug resistance profiling and plasmid stability assays. pLGP4 was resistant to six of the eight antibiotics tested and included ciprofloxacin and meropenem. The plasmid was stably maintained within host strains in the absence of an antibiotic selection. The plasmid DNA was sequenced using an Illumina MiSeq high throughput sequencing approach and assembled into contigs using SPAdes. PCR mapping and Sanger DNA sequencing of PCR amplicons was used to complete the plasmid DNA sequence. Comparative sequence analysis determined that the plasmid was similar to plasmids that have been frequently associated with multidrug resistant clinical isolates of Klebsiella spp . DNA sequence analysis showed pLGP4 harboured qnrB1 and several other antibiotic resistance genes including three β-lactamases: blaTEM-1 , blaCTX-M-15 and blaOXA-1 . The detection of a multidrug-resistant, clinically-relevant plasmid on fresh spinach emphasizes the importance for vegetable producers to implement evidence-based food safety approaches into their production practises to ensure the food safety of leafy greens.
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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 | 0.001 |
| 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 | 0.001 |
| 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".