Transcriptome profiling of mastitis-specialized Staphylococcus aureus reveals the impact of low-oxygenation on the regulation of unique pawthways after internalization into bovine mammary alveolar cell-T (MAC-T)
Bibliographic record
Abstract
Abstract Background Mastitis-specialized lineages of Staphylococcus aureus are important pathogens in the dairy industry. The molecular mechanisms underlying host- and organ-specialization in these lineages are still not fully understood. Recent findings suggested that differential expression of genes may have contributed to the evolution of strains with enhanced virulence. However, studies on gene expressions under key intra-mammary conditions are quite limited for mastitis S. aureus . The purpose of the study was to investigate the influence of low oxygen levels on the transcriptome profiles of bovine matitis S. aureus , using high-throughput whole genome qRT-PCR.Results Results showed that under normal oxygenation, a mastitis-isolate expressed subsets of genes for adaptation, environmental-sensing, and binding including merR, sigB , vraS , yycG/yycF , araC , and tetR . In addition, coupling of fermentative metabolism to virulence was indicated by accumulated transcripts for catabolite control protein A ( ccpA) and pentose-monophosphate operon and depleted transcripts for tricaroxylic acid cycle. Furthermore, sarU mediated agr activation was evidented by transcripts for toxins, adaptation, and in-vivo viability factors as staphopains and gntR operon. On the other hand, reduced oxygenation increased transcription of fibrinogen-binding genes, isd- operon, and sdrH showing aggressive adherence phenotype. While normal oxygenation produced gene activities for quick and aggressive responses, low-oxygenation induced phenotypes for persistence, binding, and metabolic inactivity.Conclusion Significant differences in the transcriptional profiles were observed for mammary alveolar cell-T (MAC-T) internalized S. aureus under low oxygen levels compared to that at normal levels. This indicated that low oxygen is an important key mammary factor that influence transcriptome profiles of intra-mammary-specific phenotypes of S. aureus . These findings will help in understanding the effect of oxygen on the differentiation and evolution of intramammary S. aureus .
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 | 0.000 |
| 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".