Degradation of <i>Listeria monocytogenes</i> biofilm by phages belonging to the genus <i>Pecentumvirus</i>
Bibliographic record
Abstract
ABSTRACT Listeria monocytogenes is a pathogenic foodborne bacterium that is a significant cause of mortality associated with foodborne illness and causes many food recalls attributed to a bacteriological cause. Their ability to form biofilms contributes to the persistence of Listeria spp. in food processing environments. When growing as biofilms, L. monocytogenes are more resistant to sanitizers used in the food industry, such as benzalkonium chloride (BAC), as well as to physical stresses like desiccation and starvation. Lytic phages of Listeria are antagonistic to a broad range of Listeria spp. and may, therefore, have utility in reducing the occurrence of Listeria -associated food recalls by preventing food contamination. We screened nine closely related Listeria phages, including the commercially available Listex P100, for host range and ability to degrade microtiter plate biofilms of L. monocytogenes ATCC 19111 (serovar 1/2a). One phage, CKA15, was selected and shown to rapidly adsorb to its host under conditions relevant to applying the phage in dairy processing environments. Under simulated dairy processing conditions (SDPC), CKA15 caused a 2-log reduction in Lm 19111 biofilm bacteria. This work supports the biosanitation potential of phage CKA15 and provides a basis for further investigation of phage-bacteria interactions in biofilms grown under SDPC. IMPORTANCE Listeria monocytogenes is a pathogenic bacterium that is especially dangerous for children, the elderly, pregnant women, and immune-compromised people. Because of this, the food industry takes its presence in their plants seriously. Food recalls due to L. monocytogenes are common with a high associated economic cost. In food-processing plants, Listeria spp. typically reside in biofilms, which are structures produced by bacteria that shield them from environmental stressors and are often attached to surfaces. The significance of our work is that we show a bacteriophage—a virus-infecting bacteria—can reduce Listeria counts by two orders of magnitude when the bacterial biofilms were grown under simulated dairy processing conditions. This work provides insights into how phages may be tested and used to develop biosanitizers that are effective but are not harmful to the environment or human health.
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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 | 0.000 | 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) | 0.001 | 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".