Identification and characterization of Staphylococcus devriesei isolates from bovine intramammary infections in KwaZulu-Natal, South Africa
Bibliographic record
Abstract
BACKGROUND: Coagulase-negative staphylococci (CoNS) are among the leading bacterial causes of bovine mastitis in many dairy-producing countries. Among the challenges associated with the specific diagnosis of CoNS infections is the biochemical heterogeneity of the species in the genus and the unavailability of accurate, cost-effective and up-to-date diagnostic tests. A previous study investigating the diversity of CoNS associated with cases of bovine mastitis in South Africa, resulted in six CoNS isolates which could not be identified despite the use of a combination of different molecular assays. The identification and characterisation of the isolates was pursued further in this study. RESULTS: The six CoNS isolates in question were identified by sequencing multiple housekeeping genes (dnaJ, hsp60, rpoB, 16S rRNA) and characterized through the use of matrix-assisted laser/desorption ionization time of flight mass spectrometry (MALDI-TOF MS) and the Biolog GEN III Microplate™ bacterial identification system. Sequencing of housekeeping genes identified the isolates as S. devriesei. This Staphylococcus species was only described in 2010 and this is the first report documenting the isolation of S. devriesei from cases of bovine IMIs in South Africa. Analysis of mass spectra generated by the six isolates showed intra-species variation which was also observed when evaluating the metabolic profiles of the isolates using the Biolog GEN III system. Neither the MALDI-TOF MS nor the Biolog database are currently populated with data relating to S. devriesei, resulting in the isolates not being identified, in the case of MALDI-TOF MS analysis, or mis-identified as was observed with the Biolog GEN III system. CONCLUSIONS: The phenotyping data collected during this investigation provides useful information concerning Staphylococcus devriesei which could be used to populate user system databases thereby ensuring the accurate identification of isolates in future. The availability of improved diagnostics will in turn facilitate studies to elucidate the epidemiology, pathogenicity and true prevalence of this species in dairy herds.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".