Identification of DNA gyrase Subunit a Mutations Associated with Ciprofloxacin Resistance in Staphylococcus aureus Isolated from Nasal Infection in Kurdistan-Iran
Bibliographic record
Abstract
Fluoroquinolone antibiotics such as ciprofloxacin are useful drugs against infections caused by Staphylococcus aureus and mutations in DNA gyrase which control bacterial DNA topology, can be one of the reason of occurrence resistance to this class of antibiotics. Therefore finding new mutations and study of the quinolone interaction with mutated GyrA can provide important issues for explanation resistance. In this study 5 ciprofloxacin resistance Staphylococcus aureus isolated among 50 collected S.aureus strains. By PCR testing, gyrA genes in resistance strains was amplified and nucleotide sequencing was done. Nucleotide sequences translate to amino acid sequences then by blastp homology between each GyrA mutant and reference GyrA were compared and mutations were recognized, at last molecular docking were done for GyrA protein and ciprofloxacin, based on free energy of binding decide if the mutations are responsible of resistance or not. The results show glutamic acid and threonine adjacent to each other in common positions 21-22, 32-33, 65-66, 84-85, 101-102, 106-107, 128-129 and 138-139 in all 5 strains were inserted . In order to finding association between mutations and ciprofloxacin resistance molecular docking by Molegro Virtual Docker 5.5 was done. Free energy of binding between reference GyrA- ciprofloxacin and mutant GyrA- ciprofloxacin were -92.3477 and -73.1642 respectively. We conclude different mutations can be affected structure of GyrA and make ciprofloxacin resistance. Finding these kinds of mutations are important and preventing them is indispensable.
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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 | 0.001 | 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".