Nitrosothiols in Bacterial Pathogens and Pathogenesis
Bibliographic record
Abstract
SIGNIFICANCE: The formation and degradation of S-nitrosothiols (SNOs) are important mechanisms of post-translational protein modification and appear to be ubiquitous in biology. These processes play well-characterized roles in eukaryotic cells, including a variety of pathologies and in relation to chronic conditions. We know little of the roles of these processes in pathogenic and other bacteria. RECENT ADVANCES: It is clear, mostly from growth and transcriptional studies, that bacteria sense and respond to exogenous SNOs. These responses are phenotypically and mechanistically distinct from the responses of bacteria to nitric oxide (NO) and NO-releasing agents, as well as peroxynitrite. Small SNOs, such as S-nitrosoglutathione (GSNO), are accumulated by bacteria with the result that intracellular S-nitrosoproteins (the 'S-nitrosoproteome') are detectable. Recently, conditions for endogenous SNO formation in enterobacteria have been described. CRITICAL ISSUES: The propensity of intracellular proteins to form SNOs is presumably constrained by the same rules of selectivity that have been discovered in eukaryotic systems, but is also influenced by uniquely bacterial NO detoxification systems, exemplified by the flavohemoglobin Hmp in enterobacteria and NO reductase of meningococci. Furthermore, the bacterial expression of such proteins impacts upon the formation of SNOs in mammalian hosts. FUTURE DIRECTIONS: The impairment during bacterial infections of specific SNO events in the mammalian host is of considerable interest in the context of proteins involved in innate immunity and intracellular signalling. In bacteria, numerous mechanisms of S-nitrosothiol degradation have been reported (e.g., GSNO reductase); others are thought to operate, based on consideration of their mammalian counterparts. The nitrosothiols of bacteria and particularly of pathogens warrant more intensive investigation.
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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) | 0.002 | 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 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".