The Effect of Genetic Background and Environment on Plasmid Fitness and Persistence
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is a major threat to public health, which, left unchecked, will have severe impacts on mortality.Plasmids are extrachromosomal DNA elements often capable of self-transmission to new hosts, and often carry AMR determinants.They are frequently deleterious and thus predicted to be lost to purifying selection.However, compensatory evolution, selection, and conjugation of the plasmid can stabilize it within populations, thus helping maintain AMR genes.In this thesis, I assess how bacterial hostplasmid fitness informs the strategies used for plasmid maintenance, compensatory evolution, and parallel evolution in a short-and long-term evolution experiment, as well as the impact of environment on plasmid fitness and resistance.In Chapter 3, I transferred the AMR plasmid pPB29 into six E. coli hosts and measured fitness before evolving each host-plasmid pair for 100 generations without antibiotic selection for the plasmid.I show that conjugation and compensatory evolution both contribute to plasmid maintenance, as conjugation of costly plasmids in mixed culture was frequent, and compensatory evolution was observed occasionally in monoculture.This shows the importance of fitness in determining how plasmids might be maintained within populations.In Chapter 4, I show that the fitness of three E. coli hosts carrying pPB29 increased over 500 generations following selection in varied concentrations of antibiotic, though fitness between cells evolved in those conditions did not vary significantly.I observed parallel evolution from phenotype to nucleotide level changes, with many transcription/translation-related mutations observed, suggesting a potential mechanism for the costliness of pPB29.Finally, in Chapter 5, I constructed six host-plasmid pairs with plasmids encoding either kanamycin or carbapenem resistance.I measured their iii fitness in twelve discrete environments where I varied three factors: the presence/absence of oxygen, pH, and glucose concentration.I found that gene-by-environment interactions were important determinants for fitness, and that environment can mediate resistance in these strains.These results highlight the importance of studying plasmids in a more integrated way, since various factors, like starting fitness, level of plasmid selection, and environment can all act to shape the trajectory of plasmid-carrying strains, and, ultimately, the threat they pose in the fight against AMR. Statement of ContributionThe thesis, "The Effect of Genetic Background and Environment on Plasmid Fitness and Persistence" is comprised of a review paper and three studies.Chapter 2, "Plasmid persistence: costs, benefits, and the plasmid paradox", is a review paper highlighting the main theory and results in the literature about plasmid maintenance.This was written by me with contributions from Dr. Alex Wong.This is a copy of the following paper: Carroll and Wong.2018.Plasmid persistence: costs, benefits, and the plasmid paradox.Can.J.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".