Stress survival islet 1 contributes to serotype-specific differences in biofilm formation in <i>Listeria monocytogenes</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Listeria monocytogenes has a significant impact on the food industry by forming biofilms on food-processing equipment. Tandem analysis of whole-genome sequencing data with biofilm data from 166 environmental and food-related L. monocytogenes isolates has revealed serotypic and genetic factors that strongly correlate with adherence and biofilm formation, such as lineage, plasmid harbourage, a three-codon deletion in inlA and the presence of the stress survival islet 1 (SSI-1). Strains from serotype 1/2b, the majority of which contained SSI-1, formed the strongest biofilms, while serotype 4b strains, the majority of which did not contain SSI-1, formed the weakest biofilms. When serotype 1/2a was separated by its SSI-1 genotype, SSI-1-positive 1/2a strains demonstrated significantly higher capacity for biofilm formation after 3 days of growth at 30°C (P < 0·0001). Together, these findings indicate that SSI-1 may contribute to serotype-associated differences in the biofilm-forming capacity in L. monocytogenes. SIGNIFICANCE AND IMPACT OF THE STUDY: Parallel analysis of whole-genome sequences and serotype-specific data was performed to identify genetic markers that correlate with increased adherence and biofilm formation in L. monocytogenes. The analyses revealed the hitherto unrecognized role of SSI-1 in biofilm formation, contributing to deeper understanding of genetic factors that influence behaviour of the species in the food processing environment..
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.
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 | 0.001 | 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 it