Bifidobacteria isolated from vaginal and gut microbiomes are indistinguishable by comparative genomics
Bibliographic record
Abstract
Bifidobacteria colonize the human gastrointestinal tract, vagina, oral cavity and breast milk. They influence human physiology and nutrition through health-promoting effects, play an important role as primary colonizers of the newborn gut, and contribute to vaginal microbiome homeostasis by producing lactic acid. Nevertheless, the mechanisms by which bifidobacteria are transmitted from mother to infant remains in discussion. Moreover, studies have suggested that Bifidobacterium spp. have specializations for gut colonization, but comparisons of strains of the same bifidobacteria species from different body sites are lacking. Here, our objective was to compare the genomes of Bifidobacterium breve (n = 17) and Bifidobacterium longum (n = 26) to assess whether gut and vaginal isolates of either species were distinguishable based on genome content. Comparison of the general genome features showed that vaginal and gut isolates did not differ in size, GC content, number of genes and CRISPR, either for B. breve or B. longum. Average nucleotide identity and whole genome phylogeny analysis revealed that vaginal and gut isolates did not cluster separately. Vaginal and gut isolates also had a similar COG (Cluster of Orthologous Group) category distribution. Differences in the accessory genomes between vaginal and gut strains were observed, but were not sufficient to distinguish isolates based on their origin. The results of this study support the hypothesis that the vaginal and gut microbiomes are colonized by a shared community of Bifidobacterium, and further emphasize the potential importance of the maternal vaginal microbiome as a source of infant gut microbiota.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".