Suppression of Intestinal Epithelial Cell Chemokine Production by Lactobacillus rhamnosus R0011 and Lactobacillus helveticus R0389 Is Mediated by Secreted Bioactive Molecules
Bibliographic record
Abstract
Host intestinal epithelial cells (IEC) present at the gastrointestinal interface are exposed to pathogenic and non-pathogenic bacteria and their products. Certain probiotic lactic acid bacteria (LAB) have been associated with a range of host-immune modulatory activities including down-regulation of pro-inflammatory gene expression and cytokine production by IEC, with growing evidence suggesting that these bacteria secrete bioactive molecules with immunomodulatory activity. The aim of this study was to determine whether two lactobacilli with immunomodulatory activity (Lactobacillus rhamnosus R0011 (Lr) and Lactobacillus helveticus R0389 (Lh)), produce soluble mediators able to influence IEC responses to Pattern Recognition Receptor (PRR) ligands and pro-inflammatory cytokines (Tumor Necrosis Factor α (TNFα), Interleukin-1β (IL-1β)), signals inducing IEC chemokine production during infection. To this end, the effects of cell-free supernatants (CFS) from Lr and Lh on IEC production of the pro-inflammatory chemokines interleukin (IL)-8 and cytokine-induced neutrophil chemoattractant 1 (CINC-1) induced by a range of host- or pathogen-derived pro-inflammatory stimuli were determined, and the impact on human HT-29 IEC and a primary IEC line (rat IEC-6) was compared. The Lr-CFS and Lh-CFS did not significantly modulate basal IL-8 production from HT-29 IECs or CINC-1 production from IEC-6 cells. However, both Lr-CFS and Lh-CFS significantly down-regulated IL-8 production from HT-29 IECs challenged with varied PRR ligands. Lr-CFS and Lh-CFS had differential effects on PRR-induced CINC-1 production by rat IEC-6 IECs, with no significant down-regulation of CINC-1 observed from IEC-6 IECs cultured with Lh-CFS. Further analysis of the Lr-CFS revealed down-regulation of IL-8 production induced by the pro-inflammatory cytokines IL-1β and TNFα Preliminary characterization of the bioactive constituent(s) of the Lr-CFS indicates that it is resistant to treatment with DNase, RNase, and an acidic protease, but is sensitive to alterations in pH. Taken together, these results indicate that these lactobacilli secrete bioactive molecules of low molecular weight that may modulate host innate immune activity through interactions with IEC.
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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".