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Record W2970346595 · doi:10.30699/mmlj17.3.1.30

Prediction of Toxin-Antitoxin system (TA system) as a Novel Potent Target in Salmonella typhi Using Bioinformatics Analysis

2020· article· en· W2970346595 on OpenAlexvenueno aff
Mahsa Jalili

Bibliographic record

VenueModern Medical Laboratory Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsAntitoxinSalmonella typhiSalmonellaToxinMicrobiologyBiologyComputational biologyEscherichia coliBacteriaGeneticsGene

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.026
GPT teacher head0.265
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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