The flagellin gene and protein from the brewing spoilage bacteria<i>Pectinatus cerevisiiphilus</i>and<i>Pectinatus frisingensis</i>
Bibliographic record
Abstract
Flagellin genes from the anaerobic Gram-negative beer-spoilage bacteria Pectinatus cerevisiiphilus and Pectinatus frisingensis were sequenced and the flagellin proteins initially characterized. Protein microsequencing led to the design of two degenerate PCR primers that allowed the P. cerevisiiphilus flagellin gene to be partially sequenced. A combination of PCR and Bubble PCR was then used to sequence the flagellin genes of three isolates from each species. Cloning and gene expression, followed by immunoblotting, confirmed the gene identities as flagellin. Analysis of the gene sequences revealed proteins similar to other bacterial flagellins, including lengths of 446 or 448 amino acids, putative sigma 28 promoters, and a termination loop. Antibody binding studies with isolated flagella correlated with gene sequence comparisons, with both indicating that the P. cerevisiiphilus isolates studied are very similar but that the P. frisingensis isolates show greater variation. Purified flagellins were found to be glycosylated, probably through an O linkage. Phylogenetic analysis revealed greater diversity within the flagellin sequences than within the 16S rRNA genes. Despite the Gram-negative morphology of Pectinatus, this genus proved most closely related to Gram-positive Firmicutes.
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) | 0.001 | 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".