Shaving and breaking bacterial chains with a viscous flow
Bibliographic record
Abstract
Some food and ferment manufacturing steps such as spray-drying result in the application of viscous stresses to bacteria. This study explores how a viscous flow impacts both bacterial adhesion functionality and bacterial cell organization using a combined experimental and modeling approach. As a model organism we study Lactobacillus rhamnosus GG (LGG) "wild type" (WT), known to feature strong adhesive affinities towards beta-lactoglobulin thanks to pili produced by the bacteria on cell surfaces, along with three cell-surface mutant strains. Applying repeated flows with high shear-rates reduces bacterial adhesive abilities up to 20% for LGG WT. Bacterial chains are also broken by this process, into 2-cell chains at low industrial shear rates, and into single cells at very high shear rates. To rationalize the experimental observations we study numerically and analytically the Stokes equations describing viscous fluid flow around a chain of elastically connected spheroidal cell bodies. In this model setting we examine qualitatively the relationship between surface traction (force per unit area), a proxy for pili removal rate, and bacterial chain length (number of cells). Longer chains result in higher maximal surface tractions, particularly at the chain extremities, while inner cells enjoy a small protection from surface tractions due to hydrodynamic interactions with their neighbors. Chain rupture therefore may act as a mechanism to preserve surface adhesive functionality in bacteria.
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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) | 0.011 | 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; both teacher heads agree on what is shown here.
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".