Beyond Genes: Non-Canonical Mechanisms Driving Antimicrobial Resistance in Bacteria
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is traditionally discussed in the context of horizontally acquired resistance genes and point mutations at target loci. However, this gene-centred model fails to account for a large number of clinically important modalities of resistance. There is now substantial evidence implicating bacteria in the ability to escape the effects of antibiotics in a variety of non-canonical ways, which are not considered in traditional diagnostic and surveillance pipelines. Among these factors, we can list those arising from global regulatory networks, phase variability, epigenetic tuning, small RNAs, genome structural variability, and phenotypic states like tolerance and persistence. This review will blend the current knowledge on these alternative pathways of resistance and underscore how they intersect with canonical genetic determinants. We will highlight cases where resistance emerges in the absence of known resistance genes, analyse the role of regulatory plasticity in efflux pump expression and membrane remodelling, and examine the contributions of bacterial stress responses and post-transcriptional control. Additionally, we will address methodological gaps in the detection of these mechanisms and their implications for clinical treatment failure, resistance surveillance, and drug development. By integrating insights from molecular microbiology, systems biology, and genomics, this review aims to offer a framework for understanding AMR as a multifaceted, context-dependent phenotype, not merely a genotype. We conclude by identifying knowledge gaps and suggesting priorities for research and diagnostic innovation in this evolving field.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".