Single-cell force spectroscopy of pili-mediated adhesion
Bibliographic record
Abstract
Although bacterial pili are known to mediate cell adhesion to a variety of substrates, the molecular interactions behind this process are poorly understood. We report the direct measurement of the forces guiding pili-mediated adhesion, focusing on the medically important probiotic bacterium Lactobacillus rhamnosus GG (LGG). Using non-invasive single-cell force spectroscopy (SCFS), we quantify the adhesion forces between individual bacteria and biotic (mucin, intestinal cells) or abiotic (hydrophobic monolayers) surfaces. On hydrophobic surfaces, bacterial pili strengthen adhesion through remarkable nanospring properties, which - presumably - enable the bacteria to resist high shear forces under physiological conditions. On mucin, nanosprings are more frequent and adhesion forces larger, reflecting the influence of specific pili-mucin bonds. Interestingly, these mechanical responses are no longer observed on human intestinal Caco-2 cells. Rather, force curves exhibit constant force plateaus with extended ruptures reflecting the extraction of membrane nanotethers. These single-cell analyses provide novel insights into the molecular mechanisms by which piliated bacteria colonize surfaces (nanosprings, nanotethers), and offer exciting avenues in nanomedicine for understanding and controlling the adhesion of microbial cells (probiotics, pathogens).
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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 | 0.001 | 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 | 0.000 |
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".