Effect of subtherapeutic and therapeutic sulfamethazine concentrations on transcribed genes and translated proteins involved in <i>Microbacterium</i> sp. C448 resistance and degradation
Bibliographic record
Abstract
Microbacterium sp. C448, isolated from a soil regularly exposed to sulfamethazine (SMZ), can use various sulphonamide antibiotics as the sole carbon source for growth. The basis for the regulation of genes encoding the sulphonamide metabolism pathway, the dihydropteroate synthase sulphonamide target (folP), and the sulphonamide resistance (sul1) genes is unknown in this organism. In the present study, the response of the transcriptome and proteome of Microbacterium sp. C448 following exposure to subtherapeutic (33 µM) or therapeutic (832 µM) SMZ concentrations was evaluated. Therapeutic concentration induced the highest sad expression and Sad production, consistent with the activity of SMZ degradation observed in cellulo. Following complete SMZ degradation, Sad production tended to return to the basal level observed prior to SMZ exposure. Transcriptomic and proteomic kinetics were concomitant for the resistance genes and proteins. The abundance of Sul1 protein, 100-fold more abundant than FolP protein, did not change in response to SMZ exposure. Moreover, non-targeted analyses highlighted the increase of a deaminase RidA and a putative sulphate exporter expression and production. These two novel factors involved in the 4-aminophenol metabolite degradation and the export of sulphate residues formed during SMZ degradation, respectively, provided new insights into the Microbacterium sp. C448 SMZ detoxification process.
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".