Host-dependent resistance of Group A Streptococcus to sulfamethoxazole mediated by a horizontally-acquired reduced folate transporter
Bibliographic record
Abstract
Described antimicrobial resistance mechanisms enable bacteria to avoid the direct effects of antibiotics and can be monitored by in vitro susceptibility testing and genetic methods. Here we describe a mechanism of sulfamethoxazole resistance that requires a host metabolite for activity. Using a combination of in vitro evolution and metabolic rescue experiments, we identify an energy-coupling factor (ECF) transporter S component gene (thfT) that enables Group A Streptococcus to acquire extracellular reduced folate compounds. ThfT likely expands the substrate specificity of an endogenous ECF transporter to acquire reduced folate compounds directly from the host, thereby bypassing the inhibition of folate biosynthesis by sulfamethoxazole. As such, ThfT is a functional equivalent of eukaryotic folate uptake pathways that confers very high levels of resistance to sulfamethoxazole, yet remains undetectable when Group A Streptococcus is grown in the absence of reduced folates. Our study highlights the need to understand how antibiotic susceptibility of pathogens might function during infections to identify additional mechanisms of resistance and reduce ineffective antibiotic use and treatment failures, which in turn further contribute to the spread of antimicrobial resistance genes amongst bacterial pathogens.
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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".