Exploring suppression subtractive hybridization (SSH) for discriminating Lactococcus lactis ssp. cremoris SK11 and ATCC 19257 in mixed culture based on the expression of strain-specific genes
Bibliographic record
Abstract
AIM: An approach based on quantitative reverse transcriptase PCR (RT-qPCR) was developed for monitoring two strains of lactococci in co-culture in milk by measuring the expression of specific genes identified by suppression subtractive hybridization (SSH). METHODS AND RESULTS: SSH was used to identify strain-specific genes of Lactococcus lactis ssp. cremoris SK11 and ATCC 19257. RT-qPCR was then employed to validate gene specificity and compare the expression of selected specific genes (glycosyltransferase and amidase genes for L. lactis ssp. cremoris ATCC 19257 and a hypothetical protein for SK11) identified by SSH. The time profile of changes in gene expression relative to ldh transcription differed between pure and mixed cultures as well as between media. At the stationary phase, gene expression of mixed cultures in GM17 attained the highest proportion of ldh transcription while mixed cultures in milk peaked at the postexponential phase. Strain ratios expressed as RNA proportion appear to favour SK11 in GM17 medium, while ATCC 19257 dominated in milk co-cultures. CONCLUSIONS: This approach was useful to determine the contribution of strain SK11 in relation to strain ATCC 19257 during co-culture in milk compared to rich medium. SIGNIFICANCE AND IMPACT OF THE STUDY: The ability to track the metabolic contribution of each lactococcal strain during fermentation of milk or cheese ripening will extend our understanding of the impact of process parameters on the production performance of strains.
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".