Characterization of high density monolayers of the biofilm bacterium<i>Caulobacter crescentus</i>: Evaluating prospects for developing immobilized cell bioreactors
Bibliographic record
Abstract
Caulobacters are biofilm-forming members of the natural flora of soil and aquatic environments, which exhibit several characteristics that make them attractive for development of high surface area microbial bioreactors or biosensors. Although caulobacters are well characterized genetically, little is known about their biofilm-forming characteristics as a monoculture, or their tolerance of bioreactor-like conditions. Here we investigated the ability of caulobacters to spontaneously form high-density monolayers on artificial surfaces under a variety of environmental conditions, using phase contrast image analysis to assess biofilm density, and epifluorescence with the vital stain DiBAC to assess viability. With adequate nutrition, extremely dense monolayers formed within 24-48 h, and maintained near 100% viability in experiments ranging up to 22 days. When areas were abraded to remove cells, repopulation occurred rapidly with characteristics similar to the population of a clean surface. When established monolayers were starved for nutrients, a significant fraction of the cells detached from the surface, and cells remaining on the surface no longer tested as viable. Within 4-6 h of nutrient restoration, however, cells in the monolayer again appeared normal and tested as 100% viable. This is the first demonstration that Caulobacter crescentus is stable and amenable to high density monolayer growth and resists starvation, though some cells may express a programmed response to detach from the surface under severe nutrient limitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".