Assessment of antimicrobial resistance in marine environments of Prince Edward Island using a selected bacterial group
Bibliographic record
Abstract
Antimicrobial resistance (AMR) in the aquatic environment is a common concern associated with urban, industrial and farm effluents. Naturally resistant bacteria have also been reported from environments without anthropogenic influence. Different approaches have been done to evaluate AMR in marine environments mostly assessing the frequency of resistance (FR) of a wide variety of heterotrophic bacteria. The study of a particular group of bacteria and the understanding of the different factors that influence AMR in marine environments would contribute in developing a more accurate method of assessment. The main objective of this thesis was to select a bacterium or a specific group of bacteria able to be used for assessing the level of AMR in different marine environments. Bacterial flora from 18 duplicated samples of sediments and pooled mussels from 3 different marine sites of Prince Edward Island, obtained during 2 seasons, were prescreened in the selective media Thiosulphate Citrate Bile Sucrose (TCBS) containing 50 μg/mL oxytetracycline (OTC) and FRs were obtained. Screened bacteria were identified by means of 3 different methods: conventional, automated (Biolog®) and analysis of 16S rDNA sequence similarity. Finally, the susceptibility of selected bacteria to 19 antibiotics was assessed using disk diffusion tests and interpreted according to season and the bacterial genus. The FR values significantly varied with the site (P < 0.001), type of sample (P < 0.001) and season (P = 0.01). During the warm season, FR values were highest in sediments of the urban-influenced site (78.9%) and in mussels of the mussel-abundant site (68.1%). Anthropogenic pollution, in the former site, and mussel bacterial selection, in the latter site, are believed to influence the FR values. However, in general, cold temperatures appeared to select for OTC-resistant bacteria. From these results, the bacterial flora from sediments appears to be a more accurate indicator of the FR to OTC in marine environments. Complementary information gained from different methods allowed the identification of the bacterial isolates to level of genus in most cases. The genera Vibrio and Shewanella constituted the majority of the bacterial flora from mussels and sediments, respectively, in which V. splendidus appeared to be common at all sites. More than 90% of all isolates showed non susceptibility to streptomycin. Almost 45% of the isolates had intermediate susceptibility to erythromycin, whereas up to 25% of the isolates showed non susceptibility to ampicillin, amoxicillin/clavulanic acid, carbenicillin, cephalothin, oxolinic acid, gentamicin and amikacin. All isolates were susceptible to cefotaxime, some fluoroquinolones, tetracyclines, potentiated sulfonamides, and phenicols. The percentage of non susceptible isolates to streptomycin was high and constant regardless of the season and bacterial genus in contrast to other antibiotics. Among Shewanella isolates, higher percentages of non susceptibility were mostly observed in those recovered during the warm season whereas among Vibrio isolates the percentages of non susceptible isolates were similar in both seasons and generally higher than for Shewanella isolates. Vibrio isolates were more frequently non susceptible to multiple antibiotics than Shewanella isolates. The susceptibility of all the isolates to the tetracyclines suggests that although 50 μg/mL OTC exerted some degree of selectivity in TCBS the selected flora has only a low level resistance. The E test showed that the activity of OTC is significantly decreased in TCBS in comparison to Mueller-Hinton agar 1.5% NaCl and that Shewanella tolerates higher concentrations of OTC than Vibrio isolates in both media but more efficiently in TCBS.
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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 | 0.001 | 0.001 |
| 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".