Enterocyte Cytoskeleton Changes Are Crucial for Enhanced Translocation of Nonpathogenic<i>Escherichia coli</i>across Metabolically Stressed Gut Epithelia
Bibliographic record
Abstract
Substantial data implicate the commensal flora as triggers for the initiation of enteric inflammation or inflammatory disease relapse. We have shown that enteric epithelia under metabolic stress respond to nonpathogenic bacteria by increases in epithelial paracellular permeability and bacterial translocation. Here we assessed the structural basis of these findings. Confluent filter-grown monolayers of the human colonic T84 epithelial cell line were treated with 0.1 mM dinitrophenol (which uncouples oxidative phosphorylation) and noninvasive, nonpathogenic Escherichia coli (strain HB101, 10(6) CFU) with or without pretreatment with various pharmacological agents. At 24 h later, apoptosis, tight-junction protein expression, transepithelial resistance (TER; a marker of paracellular permeability), and bacterial internalization and translocation were assessed. Treatment with stabilizers of microtubules (i.e., colchicine), microfilaments (i.e., jasplakinolide) and clathrin-coated pit endocytosis (i.e., phenylarsine oxide) all failed to block DNP+E. coli HB101-induced reductions in TER but effectively prevented bacterial internalization and translocation. Neither the TER defect nor the enhanced bacterial translocations were a consequence of increased apoptosis. These data show that epithelial paracellular and transcellular (i.e., bacterial internalization) permeation pathways are controlled by different mechanisms. Thus, epithelia under metabolic stress increase their endocytotic activity that can result in a microtubule-, microfilament-dependent internalization and transcytosis of bacteria. We speculate that similar events in vivo would allow excess unprocessed antigen and bacteria into the mucosa and could evoke an inflammatory response by, for example, the activation of resident or recruited immune cells.
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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 | 0.000 | 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) | 0.000 | 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".