Listeria monocytogenes Biofilms Are Planktonic Cell Factories despite Peracetic Acid Exposure under Continuous Flow Conditions
Bibliographic record
Abstract
Listeria monocytogenes biofilms are ubiquitous in the food-processing environment, where they frequently show resistance against treatment with disinfectants such as peracetic acid (PAA) due to sub-lethal damage resulting in biofilm persistence or the formation of secondary biofilms. L. monocytogenes serovar ½a EGD-e biofilms were cultivated under continuous flow conditions at 10 °C, 22 °C, and 37 °C and exposed to industrially relevant PAA concentrations. The effect of PAA on biofilm metabolic activity and biomass was monitored in real-time using the CEMS-BioSpec system, in addition to daily measurement of biofilm-derived planktonic cell production. Biofilm-derived planktonic cell yields proved to be consistent with high yields during biofilm establishment (≥106 CFU.mL−1). The exposure of biofilms to the minimum inhibitory PAA concentration (0.16%) resulted in only a brief disruption in whole-biofilm metabolic activity and biofilm biomass accumulation. The recovered biofilm accumulated more biomass and greater activity, but cell yields remained similar. Increasing concentrations of PAA (0.50%, 1.5%, and 4.0%) had a longer-lasting inhibitory effect. Only the maximum dose resulted in a lasting inhibition of biofilm activity and biomass–a factor that needs due consideration in view of dilution in industrial settings. Better disinfection monitoring tools and protocols are required to adequately address the problem of Listeria biofilms in the food-processing environment, and more emphasis should be placed on biofilms serving as a “factory” for cell proliferation rather than only a survival mechanism.
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 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".