Comparative genomics of human Lactobacillus crispatus isolates reveals genes for glycosylation and glycogen degradation: implications for in vivo dominance of the vaginal microbiota
Bibliographic record
Abstract
BACKGROUND: A vaginal microbiota dominated by lactobacilli (particularly Lactobacillus crispatus) is associated with vaginal health, whereas a vaginal microbiota not dominated by lactobacilli is considered dysbiotic. Here we investigated whether L. crispatus strains isolated from the vaginal tract of women with Lactobacillus-dominated vaginal microbiota (LVM) are pheno- or genotypically distinct from L. crispatus strains isolated from vaginal samples with dysbiotic vaginal microbiota (DVM). RESULTS: We studied 33 L. crispatus strains (n = 16 from LVM; n = 17 from DVM). Comparison of these two groups of strains showed that, although strain differences existed, both groups degraded various carbohydrates, produced similar amounts of organic acids, inhibited Neisseria gonorrhoeae growth, and did not produce biofilms. Comparative genomics analyses of 28 strains (n = 12 LVM; n = 16 DVM) revealed a novel, 3-fragmented glycosyltransferase gene that was more prevalent among strains isolated from DVM. Most L. crispatus strains showed growth on glycogen-supplemented growth media. Strains that showed less-efficient (n = 6) or no (n = 1) growth on glycogen all carried N-terminal deletions (respectively, 29 and 37 amino acid deletions) in a putative pullulanase type I protein. DISCUSSION: L. crispatus strains isolated from LVM were not phenotypically distinct from L. crispatus strains isolated from DVM; however, the finding that the latter were more likely to carry a 3-fragmented glycosyltransferase gene may indicate a role for cell surface glycoconjugates, which may shape vaginal microbiota-host interactions. Furthermore, the observation that variation in the pullulanase type I gene is associated with growth on glycogen discourages previous claims that L. crispatus cannot directly utilize glycogen.
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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 | 0.001 |
| 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".