Commensal Bacteria and Expression of Two Major Intestinal Chemokines, TECK/CCL25 and MEC/CCL28, and Their Receptors
Bibliographic record
Abstract
BACKGROUND: CCL25/TECK and CCL28/MEC are CC chemokines primarily expressed in thymic dendritic cells and mucosal epithelial cells. Their receptors, CCR9 and CCR10, are mainly expressed on T and B lymphocytes. In human, mouse, pig and sheep CCL25 and CCL28 play an important role in the segregation and the compartmentalization of the mucosal immune system. As evidenced by early comparisons of germ-free and conventional animals, the intestinal bacterial microflora has a marked effect on host intestinal immune functions. However, little is known about the impact of bacterial colonization on constitutive and induced chemokine expressions as well as on the generation of anti-inflammatory mechanisms. METHODOLOGY/PRINCIPAL FINDINGS: Therefore, we decided to focus by qPCR on the mRNA expression of two main gut chemokines, CCL25 and CCL28, their receptors CCR9 and CCR10, the Tregs marker Foxp3 and anti-inflammatory cytokines TGF-beta and IL-10 following colonization with different bacterial species within the small intestine. To accomplish this we used an original germ-free neonatal pig model and monoassociated pigs with a representative Gram-negative (Escherichia coli) or Gram-positive (Lactobacillus fermentum) commensal bacteria commonly isolated from the neonatal pig intestine. Our results show a consistent and marked effect of microbial colonization on the mRNA expression of intestinal chemokines, chemokine receptors, Foxp3 and TGF-beta. Moreover, as evidenced by in vitro experiments using two different cell lines, the pattern of regulation of CCL25 and CCL28 expression in the gut appears complex and suggests an additional role for in vivo factors. CONCLUSIONS/SIGNIFICANCE: Taken together, the results highlight the key role of bacterial microflora in the development of a functional intestinal immune system in an elegant and relevant model for human immune system development.
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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) | 0.002 | 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".