<i>In vivo</i> transcriptome analysis provides insights into host-dependent expression of virulence factors by <i>Yersinia entomophaga</i> MH96, during infection of <i>Galleria mellonella</i>
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Bibliographic record
Abstract
The function of microbes can be inferred from knowledge of genes specifically expressed in natural environments. Here, we report the in vivo transcriptome of the entomopathogenic bacterium Yersinia entomophaga MH96, captured during initial, septicemic, and pre-cadaveric stages of intrahemocoelic infection in Galleria mellonella. A total of 1285 genes were significantly upregulated by MH96 during infection; 829 genes responded to in vivo conditions during at least one stage of infection, 289 responded during two stages of infection, and 167 transcripts responded throughout all three stages of infection compared to in vitro conditions at equivalent cell densities. Genes upregulated during the earliest infection stage included components of the insecticidal toxin complex Yen-TC (chi1, chi2, and yenC1), genes for rearrangement hotspot element containing protein yenC3, cytolethal distending toxin cdtAB, and vegetative insecticidal toxin vip2. Genes more highly expressed throughout the infection cycle included the putative heat-stable enterotoxin yenT and three adhesins (usher-chaperone fimbria, filamentous hemagglutinin, and an AidA-like secreted adhesin). Clustering and functional enrichment of gene expression data also revealed expression of genes encoding type III and VI secretion system-associated effectors. Together these data provide insight into the pathobiology of MH96 and serve as an important resource supporting efforts to identify novel insecticidal agents.
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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 | 0.000 | 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