Molecular mechanism of plasmid-borne resistance to sulfonamides
Bibliographic record
Abstract
Abstract The sulfonamides (sulfas) are the oldest class of synthetic antibacterial that target the essential, conserved dihydropteroate synthase (DHPS) enzyme, encoded by folP , through chemical mimicry of its substrate p -aminobenzoic acid ( p ABA). Resistance has complicated their clinical utility and is widespread in pathogenic species. Resistance is mediated by acquisition of sul genes on mobile genetic elements, which code for the so-called Sul enzymes that are divergent DHPS enzymes with intrinsic sulfa-insensitivity. Even decades after the discovery of this resistance mechanism, its molecular details have not been understood. In this study, we elucidate the molecular basis for intrinsic resistance of Sul enzymes using x-ray crystallography, enzymology, mutagenesis, intrinsic tryptophan fluorescence, antibiotic susceptibility of a contemporary Δ folP strain, and adaptive laboratory evolution of folP. We show that the active sites of Sul enzymes possess a modified p ABA-interaction region based on insertion of a Phe-Gly sequence. This insertion is necessary for discrimination between p ABA and sulfonamides, more than 1000-fold loss in binding affinity of sulfas to Sul enzymes, and robust pan -sulfonamide resistance. We detect no fitness cost due to this active site modification, as it does not compromise the rate of dihydropteroate biosynthesis and complements the thymidine-auxotrophy of an E. coli folP deletion strain. Lab-evolved sulfa-resistance folP recapitulated this mechanism through the same active site insertion. Finally, we show that this insertion and a nearby loop confer increased active site flexibility of Sul enzymes relative to DHPS. These results provide a molecular foundation for revisiting DHPS-targeted antibacterials to evade resistance.
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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".