Genomic Characterization of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus Implicated in Bloodstream Infections, KwaZulu-Natal, South Africa: A Pilot Study
Bibliographic record
Abstract
Staphylococcus aureus is an opportunistic pathogen and a leading cause of bloodstream infections, with its capacity to acquire antibiotic resistance genes posing significant treatment challenges. This pilot study characterizes the genomic profiles of S. aureus isolates from patients with bloodstream infections in KwaZulu-Natal, South Africa, to gain insights into their resistance mechanisms, virulence factors, and clonal and phylogenetic relationships. Six multidrug-resistant (MDR) S. aureus isolates, comprising three methicillin-resistant S. aureus (MRSA) and three methicillin-susceptible S. aureus (MSSA), underwent whole genome sequencing and bioinformatics analysis. These isolates carried a range of resistance genes, including blaZ, aac(6′)-aph(2″), ant(9)-Ia, ant(6)-Ia, and fosB. The mecA gene, which confers methicillin resistance, was detected only in MRSA strains. The isolates exhibited six distinct spa types (t9475, t355, t045, t1265, t1257, and t7888) and varied in virulence gene profiles. Panton–Valentine leukocidin (Luk-PV) was found in one MSSA isolate. Two SCCmec types, IVd(2B) and I(1B), were identified, and the isolates were classified into four multilocus sequence types (MLSTs), with ST5 (n = 3) being the most common. These sequence types clustered into two clonal complexes, CC5 and CC8. Notably, two MRSA clones were identified: ST5-CC5-t045-SCCmec_I(1B) and the human-associated endemic clone ST612-CC8-t1257-SCCmec_IVd(2B). Phylogenomic analysis revealed clustering by MLST, indicating strong genetic relationships within clonal complexes. These findings highlight the value of genomic surveillance in guiding targeted interventions to reduce treatment failures and mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".