Alteration of the Microbiota and Virulence Gene Expression in E. coli O157:H7 in Pig Ligated Intestine with and without AE Lesions
Bibliographic record
Abstract
BACKGROUND: Previously we found that E. coli O157:H7 inoculated into ligated pig intestine formed attaching and effacing (AE) lesions in some pigs but not in others. The present study evaluated changes in the microbial community and in virulence gene expression in E. coli O157:H7 in ligated pig intestine in which the bacteria formed AE lesions or failed to form AE lesions. METHODOLOGY/PRINCIPAL FINDINGS: The intestinal microbiota was assessed by RNA-based denaturing gradient gel electrophoresis (DGGE) analysis. The DGGE banding patterns showed distinct differences involving two bands which had increased intensity specifically in AE-negative pigs (AE- bands) and several bands which were more abundant in AE-positive pigs. Sequence analysis revealed that the two AE- bands belonged to Veillonella caviae, a species with probiotic properties, and Bacteroides sp. Concurrent with the differences in microbiota, gene expression analysis by quantitative PCR showed that, compared with AE negative pigs, E. coli O157:H7 in AE positive pigs had upregulated genes for putative adhesins, non-LEE encoded nleA and quorum sensing qseF, acid resistance gene ureD, and genes from the locus of enterocyte effacement (LEE). CONCLUSIONS/SIGNIFICANCE: The present study demonstrated that AE-positive pigs had reduced activities or populations of Veillonella caviae and Bacterioides sp. compared with AE-negative pigs. Further studies are required to understand how the microbiota was changed and the role of these organisms in the control of E. coli O157:H7.
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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 | 0.001 | 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".