A Lacticaseibacillus rhamnosus secretome induces immunoregulatory transcriptional, functional and immunometabolic signatures in human THP-1 monocytes
Bibliographic record
Abstract
Abstract Macrophage responses to activation are fluid and dynamic in their ability to respond appropriately to challenges, a role integral to host defence. While bacteria can influence macrophage differentiation and polarization into pro-inflammatory and alternatively activated phenotypes through direct interactions, many questions surround indirect communication mechanisms mediated through secretomes derived from gut bacteria, such as lactobacilli. We examined effects of secretome-mediated conditioning on THP-1 human monocytes, focusing on the ability of the Lacticaseibacillus rhamnosus R0011 secretome (LrS) to drive macrophage differentiation and polarization and prime immune responses to subsequent challenge with lipopolysaccharide (LPS). Genome-wide transcriptional profiling revealed increased M2-associated gene transcription in response to LrS conditioning in THP-1 cells. Cytokine and chemokine profiling confirmed these results, indicating increased M2-associated chemokine and cytokine production (IL-1Ra, IL-10). These cells had increased cell-surface marker expression of CD11b, CD86, and CX 3 CR1, coupled with reduced expression of the M1 macrophage-associated marker CD64. Mitochondrial substrate utilization assays indicated diminished reliance on glycolytic substrates, coupled with increased utilization of citric acid cycle intermediates, characteristics of functional M2 activity. LPS challenge of LrS-conditioned THP-1s revealed heightened responsiveness, indicative of innate immune priming. Resting stage THP-1 macrophages co-conditioned with LrS and retinoic acid also displayed an immunoregulatory phenotype with expression of CD83, CD11c and CD103 and production of regulatory cytokines. Secretome-mediated conditioning of macrophages into an immunoregulatory phenotype is an uncharacterized and potentially important route through which lactic acid bacteria and the gut microbiota may train and shape innate immunity at the gut-mucosal interface.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 teacher head, 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".