Molecular characterization of arginine deiminase pathway in <scp> <i>L</i> </scp> <i>aribacter hongkongensis</i> and unique regulation of arginine catabolism and anabolism by multiple environmental stresses
Bibliographic record
Abstract
The betaproteobacterium Laribacter hongkongensis is associated with invasive bacteremic infections and gastroenteritis. Its genome contains two adjacent arc gene cassettes (arc1 and arc2) under independent transcriptional control, which are essential for acid resistance. Laribacter hongkongensis also encodes duplicate copies of the argA and argB genes from the arginine biosynthesis pathway. We show that arginine enhances the transcription of arcA2 but suppresses arcA1 expression. We demonstrate that ArgR acts as a transcriptional regulator of the two arc operons through binding to ARG operator sites (ARG boxes). Upon temperature shift from 20°C to 37°C, arcA1 transcription is upregulated while arcA2, argA2, argB2 and argG are downregulated. The transcription of arcA1 and arcA2 are augmented under anaerobic and acidic conditions. The transcription levels of argA1, argA2, argB1, argB2 and argG are significantly increased under anaerobic and acidic conditions but are repressed by the addition of arginine. Deletion of argR significantly decreases bacterial survival in macrophages, while expression of both arc operons, argR and all five of the anabolic arg genes increases 8 h post-infection. Our results show that arginine catabolism in L. hongkongensis is finely regulated by controlling the transcription of two arc operons, whereas arginine anabolism is controlled by two copies of argA and argB.
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) | 0.000 | 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 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".