A PGPR-Produced Bacteriocin for Sustainable Agriculture: A Review of Thuricin 17 Characteristics and Applications
Why this work is in the frame
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Bibliographic record
Abstract
Many prokaryotes produce and excrete bacteriocins (proteins with antimicrobial activity) to reduce competition from related strains. Bacteriocins are import in food industries, while little research has been focused on the agricultural potential of bacteriocins. Some bacteriocin producing bacteria are members of the phytomicrobiome; some strains are plant growth promoting rhizobacteria (PGPR). Thuricin 17 is a small peptide (3.162 kDa), a subclass IId bacteriocin produced by Bacillus thuringiensis NEB17, isolated from soybean nodules and thus a member of the phytomicrobiome. It is either cidal or static to a wide range of prokaryotes. In this way, it removes key competition from the niche space of the producer organism. Interestingly, thuricin 17 is not active against a wide range of rhizobial strains involved in symbiotic nitrogen fixation with legumes or against other PGPRs. In addition, it stimulates plant growth, particularly in the presence of abiotic stresses. The stresses it assists with include key ones associated with climate change (drought, high temperature, soil salinity). Hence, in the presence of stress it increases the size of the overall niche space, within plant roots, for B. thuringiensis NEB17. Through its anti-microbial activity, it could also enhance plant growth via control of specific plant pathogens. None of the isolated bacteriocins have been examined as broadly as thuricin 17 on plant growth promotion. Thus, this review focuses on the effect of thuricin 17 as a microbe to plant signal that assists crop plants in managing stress and making agricultural systems more climate change resilient.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it