The Type III Effector AvrBs2 in <i>Xanthomonas oryzae</i> pv. <i>oryzicola</i> Suppresses Rice Immunity and Promotes Disease Development
Bibliographic record
Abstract
Xanthomonas oryzae pv. oryzicola, the causal agent of bacterial leaf streak, is one of the most important bacterial pathogens in rice. However, little is known about the functions of individual type III effectors in virulence and pathogenicity of X. oryzae pv. oryzicola. Here, we examined the effect of the mutations of 23 putative nontranscription activator-like effector genes on X. oryzae pv. oryzicola virulence. The avrBs2 knock-out mutant was significantly attenuated in virulence to rice. In contrast, the xopAA deletion caused enhanced virulence to a certain rice cultivar. It was also demonstrated that six putative effectors, including XopN, XopX, XopA, XopY, XopF1, and AvrBs2, caused the hypersensitive response on nonhost Nicotiana benthamiana leaves. Virulence function of AvrBs2 was further confirmed by transgenic technology. Pathogen-associated molecular pattern-triggered immune responses including the generation of reactive oxygen species and expression of pathogenesis-related genes were strongly suppressed in the AvrBs2-expressing transgenic rice lines. Although not inhibiting flg22-induced activation of mitogen-activated protein kinases, heterologous expression of AvrBs2 greatly promotes disease progression in rice caused by two important bacterial pathogens X. oryzae pvs. oryzae and oryzicola. Collectively, these results indicate that AvrBs2 is an essential virulence factor that contributes to X. oryzae pv. oryzicola virulence through inhibiting defense responses and promoting bacterial multiplication in monocot rice.
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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 | 0.000 | 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) | 0.001 | 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".