Surface Viscoelasticity of Individual Gram-Negative Bacterial Cells Measured Using Atomic Force Microscopy
Bibliographic record
Abstract
The cell envelope of gram-negative bacteria is responsible for many important biological functions: it plays a structural role, it accommodates the selective transfer of material across the cell wall, it undergoes changes made necessary by growth and division, and it transfers information about the environment into the cell. Thus, an accurate quantification of cell mechanical properties is required not only to understand physiological processes but also to help elucidate the relationship between cell surface structure and function. We have used a novel, atomic force microscopy (AFM)-based approach to probe the mechanical properties of single bacterial cells by applying a constant compressive force to the cell under fluid conditions while measuring the time-dependent displacement (creep) of the AFM tip due to the viscoelastic properties of the cell. For these experiments, we chose a representative gram-negative bacterium, Pseudomonas aeruginosa PAO1, and we used regular V-shaped AFM cantilevers with pyramid-shaped and colloidal tips. We find that the cell response is well described by a three-element mechanical model which describes an effective cell spring constant, k(1), and an effective time constant, tau, for the creep deformation. Adding glutaraldehyde, an agent that increases the covalent bonding of the cell surface, produced a significant increase in k(1) together with a significant decrease in tau. This work represents a new attempt toward the understanding of the nanomechanical properties of single bacteria while they are under fluid conditions, which could be of practical value for elucidating, for instance, the biomechanical effects of drugs (such as antibiotics) on 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 | 0.001 |
| 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 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".