Transcriptomic response of Gordonia sp. strain NB4-1Y when provided with 6:2 fluorotelomer sulfonamidoalkyl betaine or 6:2 fluorotelomer sulfonate as sole sulfur source
Bibliographic record
Abstract
Abstract Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are environmental contaminants of concern. We previously described biodegradation of two PFAS that represent components and transformation products of aqueous film-forming foams (AFFF), 6:2 fluorotelomer sulfonamidoalkyl betaine (6:2 FTAB) and 6:2 fluorotelomer sulfonate (6:2 FTSA), by Gordonia sp. strain NB4-1Y. To identify genes involved in the breakdown of these compounds, the transcriptomic response of NB4-1Y was examined when grown on 6:2 FTAB, 6:2 FTSA, a non-fluorinated analog of 6:2 FTSA (1-octanesulfonate), or MgSO 4 , as sole sulfur source. Differentially expressed genes were identified as those with ± 1.5 log 2 -fold-differences (± 1.5 log 2 FD) in transcript abundances in pairwise comparisons. Transcriptomes of cells grown on 6:2 FTAB and 6:2 FTSA were most similar (7.9% of genes expressed ± 1.5 log 2 FD); however, several genes that were expressed in greater abundance in 6:2 FTAB treated cells compared to 6:2 FTSA treated cells were noted for their potential role in carbon–nitrogen bond cleavage in 6:2 FTAB. Responses to sulfur limitation were observed in 6:2 FTAB, 6:2 FTSA, and 1-octanesulfonate treatments, as 20 genes relating to global sulfate stress response were more highly expressed under these conditions compared to the MgSO 4 treatment. More highly expressed oxygenase genes in 6:2 FTAB, 6:2 FTSA, and 1-octanesulfonate treatments were found to code for proteins with lower percent sulfur-containing amino acids compared to both the total proteome and to oxygenases showing decreased expression. This work identifies genetic targets for further characterization and will inform studies aimed at evaluating the biodegradation potential of environmental samples through applied genomics. Graphic Abstract
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".