Comparative genomics reveals the correlations of stress response genes and bacteriophages in developing antibiotic resistance of <i>Staphylococcus saprophyticus</i>
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Bibliographic record
Abstract
ABSTRACT Staphylococcus saprophyticus is the leading Gram-positive cause of uncomplicated urinary tract infections. Recent reports of increasing antimicrobial resistance (AMR) in S. saprophyticus warrant investigation of its understudied resistance patterns. Here, we characterized a diverse collection of S. saprophyticus ( n = 275) using comparative whole genome sequencing. We performed a phylogenetic analysis of core genes (1,646) to group our S. saprophyticus and investigated the distributions of antibiotic resistance genes (ARGs). S. saprophyticus isolates belonged to two previously characterized lineages, and 14.91% (41/275) demonstrated multidrug resistance. We compared antimicrobial susceptibility phenotypes of our S. saprophyticus with the presence of different ARGs and gene alleles. 29.8% (82/275) carried staphylococcal cassette chromosome mobile elements, among which 25.6% (21/82) were mecA + . Penicillin resistance was associated with the presence of mecA or blaZ . The mecA gene could serve as a marker to infer cefoxitin and oxacillin resistance of S. saprophyticus , but the absence of this gene is not predictive of susceptibility. Utilizing computational modeling, we found several genes were associated with cefoxitin and oxacillin resistance in mecA − isolates, some of which have predicted functions in stress response and cell wall synthesis. Furthermore, phenotype association analysis indicates ARGs against non-β-lactams reported in other staphylococci may serve as resistance determinants of S. saprophyticus . Lastly, we observed that two ARGs [ erm and erm (44)v ], carried by bacteriophages, were correlated with high phenotypic non-susceptibility against erythromycin (11/11 and 10/10) and clindamycin (11/11 and 10/10). The AMR-correlated genetic elements identified in this work can help to refine resistance prediction of S. saprophyticus during antibiotic treatment. IMPORTANCE Staphylococcus saprophyticus is the second most common bacteria associated with urinary tract infections (UTIs) in women. The antimicrobial treatment regimen for uncomplicated UTI is normally nitrofurantoin, trimethoprim-sulfamethoxazole (TMP-SMX), or a fluoroquinolone without routine susceptibility testing of S. saprophyticus recovered from urine specimens. However, TMP-SMX-resistant S. saprophyticus has been detected recently in UTI patients, as well as in our cohort. Herein, we investigated the understudied resistance patterns of this pathogenic species by linking genomic antibiotic resistance gene (ARG) content to susceptibility phenotypes. We describe ARG associations with known and novel SCC mec configurations as well as phage elements in S. saprophyticus , which may serve as intervention or diagnostic targets to limit resistance transmission. Our analyses yielded a comprehensive database of phenotypic data associated with the ARG sequence in clinical S. saprophyticus isolates, which will be crucial for resistance surveillance and prediction to enable precise diagnosis and effective treatment of S. saprophyticus UTIs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it