<i>Escherichia coli</i>O157:H7 Survives within Human Macrophages: Global Gene Expression Profile and Involvement of the Shiga Toxins
Bibliographic record
Abstract
Escherichia coli O157:H7 is an important food-borne pathogen that specifically binds to the follicle-associated epithelium in the intestine, which rapidly brings this bacterial pathogen in contact with underlying human macrophages. Very little information is available about the interaction between E. coli O157:H7 and human macrophages. We evaluated the uptake and survival of strain EDL933 during infection of human macrophages. Surprisingly, EDL933 survived and multiplied in human macrophages at 24 h postinfection. The global gene expression profile of this pathogen during macrophage infection was determined. Inside human macrophages, upregulation of E. coli O157:H7 genes carried on O islands (such as pagC, the genes for both of the Shiga toxins, and the two iron transport system operons fit and chu) was observed. Genes involved in acid resistance and in the SOS response were upregulated. However, genes of the locus of enterocyte effacement or genes involved in peroxide resistance were not differentially expressed. Many genes with putative or unknown functions were upregulated inside human macrophages and may be newly discovered virulence factors. As the Shiga toxin genes were upregulated in macrophages, survival and cytotoxicity assays were performed with isogenic Shiga toxin mutants. The initial uptake of Shiga toxins mutants was higher than that of the wild type; however, the survival rates were significantly lower at 24 h postinfection. Thus, Shiga toxins are implicated in the interaction between E. coli O157:H7 and human macrophages. Understanding the molecular mechanisms used by E. coli to survive within macrophages may help in the identification of targets for new therapeutic agents.
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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".