Prediction of Toxin-Antitoxin system (TA system) as a Novel Potent Target in Salmonella typhi Using Bioinformatics Analysis
Bibliographic record
Abstract
Background and Objective: Salmonella typhi is one of the major challenges for the human and animal health.Salmonella with high pathogenicity can be harmful factor for human health.The control of this pathogen is a big challenge as it can cause serious infectious diseases such as gastroenteritis, septicemia and typhoid fever.On the other side, there are many factors such as toxin-antitoxin (TA) system which may be a regulator for the virulence factors in bacteria.The TA system as a potent target for antimicrobial therapy is very important in this bacterium.Therefore, bioinformatics analyses are essential for identification of the potent TA loci.This system is potency for the antimicrobial therapy.In this study, we focused on the TA system as a regulon for the pathogenicity of Salmonella typhi.Materials and methods: We analyzed the potent TA loci and assume the review of these potent TA loci can help us in the next experimental studies.We used RASTA (RASTA-Bacteria: a web-based tool for identifying toxin-antitoxin loci in prokaryotes) database and after that we analyzed TA system in all of the scores.Finally, all of the known and unknown TA loci were identified.Results: By scrutiny different scores and excavate potent TA loci in Salmonella typhi, we were able to discover significant potent TA loci.We discovered several loci in scores 70-80%.In other hand, the potent TA loci were significant in scores 90-100%.A significant number of potent TA loci were discovered on this score.It is interesting that hth-xre exists in most scores and finally the highest number is compared to the other unknown potent TA loci in both strains of Salmonella typhi.Conclusion: By studying all the scores in two different strains of Salmonella typhi including P_stx_12_uid87001 and Ty21a_uid201427, hth-xre was shown in both strains as an unknown TA system which can be a great help for bioinformatics and experimental studies.Finally; we identified the potent TA loci in different Salmonella typhi strains.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".