A2 USING BIOPSY-DERIVED ORGANOIDS AND GUT-ON-A-CHIP PLATFORM TO DEVELOP A PHYSIOLOGICALLY RELEVANT BACTERIAL INFECTION MODEL
Bibliographic record
Abstract
Abstract Background The intestine is a highly complex ecosystem, consisting of diverse cell types, dynamic interactions, and mechanical forces. These elements are key to maintaining intestinal homeostasis and modulating the risk of enteric bacterial infections. Traditional in vitro models fail to recapitulate the physiological complexity of the gut, limiting our understanding of bacterial pathogenesis and host responses. Patient-derived intestinal organoids offer a promising solution by replicating the cellular diversity and structure of the epithelium. However, conventional organoid cultures lack the dynamic environment present in vivo. The emergence of organ-on-a-chip technology provides an innovative approach for such modeling, by incorporating mechanical forces, such as flow and stretch, to better mimic the intestinal environment. Aims To establish a bacterial infection model using patient-derived intestinal organoids cultured in a gut-on-a-chip system to address the challenges of simulating the complex enteric pathogen-host interactions. Methods An enteric Salmonella infection model was developed using the Emulate Colon Intestine-Chip. This system consists of two parallel channels seeded with patient-derived ascending colonic organoids in the upper channel and Human Intestinal Microvascular Endothelial Cells (HIMEC) in the lower. Cellular differentiation, barrier integrity, mucus and cytokine release, and pathogen invasion was assessed. Results Biopsy-derived colonic organoids rapidly differentiated into a multi-cell type system when co-cultured with HIMEC on the Emulate Chip, showing tight junction formation and a stable epithelial barrier. Following Salmonella infection, a significant decrease in intestinal permeability was observed in infected organoids compared to uninfected controls, indicating a breach in epithelial integrity. This disruption was accompanied by release of inflammatory cytokines, including CCL2 and IL-8, demonstrating a robust innate immune response. Notably, goblet cell release of mucus into the supernatant were observed post-infection, suggesting a rapid secretion of mucus as a defense mechanism against infection. Microscopy confirmed extensive Salmonella invasion into the epithelial layer, demonstrating the organ-on-a-chip system’s ability to replicate key aspects of enteric infection as observed seen in vivo. Conclusions The Salmonella infection model established using the gut-on-a-chip platform effectively recapitulates key features of enteric infection within a physiologically relevant microenvironment. This model demonstrates the loss of epithelial integrity, the activation of robust inflammatory responses, and rapid mucus secretion, offering a powerful tool for studying host-pathogen interactions in the human gut and potentially informing therapeutic development for enteric diseases. Funding Agencies Weston Family Foundation
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".